Machine Learning Training with Python: https://www.edureka.co/data-sc....ience-python-certifi
This "Top 10 Applications of Machine Learning in 2024" video will give you an idea of how vast the machine learning is and how commonly you are using it in your day to day life.

Check out our playlist for more videos: http://bit.ly/2taym8X

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#MachineLearningApplications #MachineLearningUsingPython #MachineLearningTraining

How it Works?
1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

- - - - - - - - - - - - - - - - -
About the Course

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience.

After completing this Machine Learning Certification Training using Python, you should be able to:
Gain insight into the 'Roles' played by a Machine Learning Engineer
Automate data analysis using python
Describe Machine Learning
Work with real-time data
Learn tools and techniques for predictive modeling
Discuss Machine Learning algorithms and their implementation
Validate Machine Learning algorithms
Explain Time Series and it’s related concepts
Gain expertise to handle business in future, living the present

- - - - - - - - - - - - - - - - - - -

Why learn Machine Learning with Python?

Data Science is a set of techniques that enable the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.

For more information, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free)

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🔥 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 𝐌𝐚𝐬𝐭𝐞𝐫 𝐏𝐫𝐨𝐠𝐫𝐚𝐦(𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎): https://www.edureka.co/masters....-program/machine-lea
This Edureka video will provide you with a detailed and comprehensive knowledge of Naive Bayes Classifier Algorithm in python. At the end of the video, you will learn from a demo example on Naive Bayes. Below are the topics covered in this tutorial:
00:00:00 Introduction
00:00:25 Agenda
00:01:35 What is Machine Learning
00:13:47 Introduction to Classification
00:17:28 Classification Algorithms
00:18:30 What is Naïve Bayes
00:31:36 Mathematical Working of Naïve Bayes
00:39:24 Example

📝Feel free to comment your doubts in the comment section below, and we will be happy to answer📝

-------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧---------

🔵 DevOps Online Training:https://bit.ly/3r7xtvQ
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🌕 Java Online Training: https://bit.ly/35K5hrk
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---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬---------

🔵 DevOps Engineer Masters Program: https://bit.ly/37p4goY
🌕 Cloud Architect Masters Program: https://bit.ly/35LP0SV
🔵 Data Scientist Masters Program: https://bit.ly/3NULA1q
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🔵 Machine Learning Engineer Masters Program:https://bit.ly/3ueP9rm
🌕 Business Intelligence Masters Program: https://bit.ly/3x9qpT5
🔵 Python Developer Masters Program:https://bit.ly/3j8YYkg
🌕 RPA Developer Masters Program: https://bit.ly/3JgqQ0g
🔵 Web Development Masters Program: https://bit.ly/3KlZJT1
🌕 Computer Science Bootcamp Program : https://bit.ly/3Kg70Uh
🔵 Cyber Security Masters Program: https://bit.ly/3uo98UN
🌕 Full Stack Developer Masters Program : https://bit.ly/3NUlVGb
🔵 Automation Testing Engineer Masters Program : https://bit.ly/3E0rFcZ
🌕 Python Developer Masters Program : https://bit.ly/3j8YYkg
🔵 Azure Cloud Engineer Masters Program: https://bit.ly/3NQb9Ax

--------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐏𝗼𝘀𝘁 𝗚𝗿𝗮𝗱𝘂𝗮𝘁𝗲 𝐂𝐨𝐮𝐫𝐬𝐞𝐬--------
🔵 Artificial and Machine Learning PGD with E & ICT Academy
NIT Warangal: https://bit.ly/3Kji6bb
🌕 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3uoajDH

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟐 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩𝐓𝐨𝐩 𝟏𝟎 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟮: https://bit.ly/3yhEs7S
⏩𝐓𝐨𝐩 𝟏𝟎 𝐇𝐢𝐠𝐡𝐞𝐬𝐭 𝐏𝐚𝐲𝐢𝐧𝐠 𝐉𝐨𝐛𝐬 𝐅𝐨𝐫 𝟐𝟎𝟐𝟐: https://bit.ly/3HcpPG6
⏩𝐓𝐨𝐩 𝟏𝟎 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬 𝐟𝐨𝐫 𝟐𝟎𝟐𝟐: https://bit.ly/3FW6F69
⏩𝐓𝐨𝐩 𝟏𝟎 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝟐𝟎𝟐𝟐: https://bit.ly/3gH57mr

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
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📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_lea...
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📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?count...
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

About the Machine Learning with Python Training
Edureka’s Machine Learning Certification Training using Python is designed to make you grab the concepts of Machine Learning. This Machine Learning Certification will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in the python programming language. Furthermore, in this Machine Learning with Python Training, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of this Machine Learning online course, we will be discussing various practical use cases of Machine Learning with Python programming language to enhance your learning experience. Edureka offers the best Machine Learning Training online for those who want to be the best in Python. Enroll now with Edureka's online Machine Learning Certification to get trained with industrial experts.

What are the pre-requisites for this Machine Learning Certification Training ?
The pre-requisites for the Machine Learning Training include development experience with Python. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus. However, Python would be more advantageous.

🔥Machine Learning Training with Python: https://www.edureka.co/machine....-learning-certificat
This Edureka video on 'Mathematics for Machine Learning' teaches you all the math needed to get started with mastering Machine Learning. It teaches you all the necessary topics and concepts of Linear Algebra, Multivariate Calculus, Statistics, and Probability and also dives into the actual implementation of these topics.

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🔹Blog Series: https://bit.ly/2PX5lIp

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-------------------------Edureka Online Training and Certification-----------------------

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---------------------------Edureka Masters Programs-------------------------

🔵DevOps Engineer Masters Program: https://bit.ly/2B9tZCp
🟣Cloud Architect Masters Program: https://bit.ly/3i9z0eJ
🔵Data Scientist Masters Program: https://bit.ly/2YHaolS
🟣Big Data Architect Masters Program: https://bit.ly/31qrOVv
🔵Machine Learning Engineer Masters Program: https://bit.ly/388NXJi
🟣Business Intelligence Masters Program: https://bit.ly/2BPLtn2
🔵Python Developer Masters Program: https://bit.ly/2Vn7tgb
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-----------------------------Edureka PGP Courses----------------------------

🔵Artificial and Machine Learning PGP: https://bit.ly/2Ziy7b1
🟣CyberSecurity PGP: https://bit.ly/3eHvI0h
🔵Digital Marketing PGP: https://bit.ly/38cqdnz
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#edureka #machinelearningedureka #MathematicsforMachineLearning #MachineLearning #MachineLearningTraining #learnMachineLearning #withme

About the Course :

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience.
--------------------------------------
Why Learn Machine Learning with Python?

Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.
--------------------------------------------
Who should go for this Course?

Edureka’s Python Machine Learning Certification Course is a good fit for the below professionals:
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'Python' professionals who want to design automatic predictive models
--------------------------------
Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.
For more information, please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free).

🔥Edureka AWS Training: https://www.edureka.co/aws-certification-training
This Edureka video on "Deploy an ML Model using Amazon Sagemaker" discusses what is Amazon Sagemaker and how you can build, train and deploy your Machine Learning Models in Amazon Sagemaker.
Topics covered in this session:
00:00 Introduction
00:40 Agenda
01:18 What is Amazon Sagemaker
04:28 Create Your AWS Account
06:52 Create your first Notebook Instance
12:56 Download and Explore Dataset
17:44 Train Your Model
24:43 Deploy Your Model
26:42 Evaluate Your Model
29:09 Case Study

🔹Check Edureka's complete DevOps playlist here: http://goo.gl/O2vo13
🔹Check Edureka's Blog playlist here: https://bit.ly/3gfNuZr

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#Edureka #DeployAnMlModelUsingAmazonSagemaker #AWSTutorial #AWSCertification #AWSTraining #AWSMachineLearning #AWSMLDeployment #MachineLearningOnCloud #CloudComputing #AWS
--------------------------------------------------------------------------------------------
How it Works?
1. This is a 5 Week Instructor led Online Course.
2. Course consists of 30 hours of online classes, 30 hours of assignment, 20 hours of project
3. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
4. You will get Lifetime Access to the recordings in the LMS.
5. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

- - - - - - - - - - - - - -
About the Course

AWS Architect Certification Training from Edureka is designed to provide in depth knowledge about Amazon AWS architectural principles and its components. The sessions will be conducted by Industry practitioners who will train you to leverage AWS services to make the AWS cloud infrastructure scalable, reliable, and highly available. This course is completely aligned to AWS Architect Certification - Associate Level exam conducted by Amazon Web Services.

During this AWS Architect Online training, you'll learn:
1. AWS Architecture and different models of Cloud Computing
2. Compute Services: Amazon EC2, Auto Scaling and Load Balancing, AWS Lambda, Elastic Beanstalk
3. Amazon Storage Services : EBS, S3 AWS, Glacier, CloudFront, Snowball, Storage Gateway
4. Database Services: RDS, DynamoDB, ElastiCache, RedShift
5. Security and Identity Services: IAM, KMS
6. Networking Services: Amazon VPC, Route 53, Direct Connect
7. Management Tools: CloudTrail, CloudWatch, CloudFormation, OpsWorks, Trusty Advisor
8. Application Services: SES, SNS, SQS

Course Objectives

On completion of the AWS Architect Certification training, learner will be able to:
1. Design and deploy scalable, highly available, and fault tolerant systems on AWS
2. Understand lift and shift of an existing on-premises application to AWS
3. Ingress and egress of data to and from AWS
4. Identifying appropriate use of AWS architectural best practices
5. Estimating AWS costs and identifying cost control mechanisms

Pre-requisites

There are no specific prerequisites for this course. Any professional who has an understanding of IT Service Management can join this training. There is no programming knowledge needed and no prior AWS experience required.

If you are looking for live online training, write back to us at sales@edureka.in or call us at US: + 18338555775 (Toll-Free) or India: +91 9606058406 for more information.

🔥 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 𝐌𝐚𝐬𝐭𝐞𝐫 𝐏𝐫𝐨𝐠𝐫𝐚𝐦: https://www.edureka.co/masters....-program/machine-lea (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
This Edureka tutorial explains the 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐒𝐞𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐢𝐧 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, Various techniques used for feature selection like filter methods, wrapper methods. Embedded methods along with practical examples in Python. Explore the feature selection statistics and advantages and disadvantages of feature selection.
We will be covering the following topics in this video:
00:00:00 - Introduction
00:00:52 - Need for Feature Selection
00:02:15 - What is Feature Selection?
00:02:51 - Importance of Feature Selection
00:03:32 - Feature Selection Statistics
00:04:52 - Various Techniques
00:05:28 - Filter Method with Hands-on
00:10:20 - Wrapper Method with Hands-on
00:14:22 - Embedded Method with Hands-on
00:17:48- Advantages of Feature Selection
00:18:27 - Disadvantages of Feature Selection
📝Feel free to comment your doubts in the comment section below, and we will be happy to answer📝

-------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧---------

🔵 DevOps Online Training:https://bit.ly/3r7xtvQ
🌕 AWS Online Training: https://bit.ly/3r6sawS
🔵 Azure DevOps Online Training:https://bit.ly/3r8shaX
🌕 Tableau Online Training: https://bit.ly/3LMOLGE
🔵 Power BI Online Training: https://bit.ly/3J9uOrP
🌕 Selenium Online Training: https://bit.ly/3jeSvEx
🔵 PMP Online Training: https://bit.ly/3DNgUKX
🌕 Salesforce Online Training: https://bit.ly/3j8VyxW
🔵 Cybersecurity Online Training: https://bit.ly/3LJBoGV
🌕 Java Online Training: https://bit.ly/35K5hrk
🔵 Big Data Online Training: https://bit.ly/3ugVAua
🌕 RPA Online Training: https://bit.ly/3LIqcKT
🔵 Python Online Training:https://bit.ly/3jbsAxr
🌕 Azure Online Training:https://bit.ly/3j8WOBa
🔵 GCP Online Training: https://bit.ly/3LHJb8g
🌕 Microservices Online Training:https://bit.ly/3r7Xwmt
🔵 Data Science Online Training: https://bit.ly/3r9dgFX

---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬---------

🔵 DevOps Engineer Masters Program: https://bit.ly/37p4goY
🌕 Cloud Architect Masters Program: https://bit.ly/35LP0SV
🔵 Data Scientist Masters Program: https://bit.ly/3NULA1q
🌕 Big Data Architect Masters Program:https://bit.ly/38qZTud
🔵 Machine Learning Engineer Masters Program:https://bit.ly/3ueP9rm
🌕 Business Intelligence Masters Program: https://bit.ly/3x9qpT5
🔵 Python Developer Masters Program:https://bit.ly/3j8YYkg
🌕 RPA Developer Masters Program: https://bit.ly/3JgqQ0g
🔵 Web Development Masters Program: https://bit.ly/3KlZJT1
🌕 Computer Science Bootcamp Program : https://bit.ly/3Kg70Uh
🔵 Cyber Security Masters Program: https://bit.ly/3uo98UN
🌕 Full Stack Developer Masters Program : https://bit.ly/3NUlVGb
🔵 Automation Testing Engineer Masters Program : https://bit.ly/3E0rFcZ
🌕 Python Developer Masters Program : https://bit.ly/3j8YYkg
🔵 Azure Cloud Engineer Masters Program: https://bit.ly/3NQb9Ax

--------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐏𝗼𝘀𝘁 𝗚𝗿𝗮𝗱𝘂𝗮𝘁𝗲 𝐂𝐨𝐮𝐫𝐬𝐞𝐬--------
🔵 Artificial and Machine Learning PGD with E & ICT Academy
NIT Warangal: https://bit.ly/3Kji6bb
🌕 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3uoajDH

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟐 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩𝐓𝐨𝐩 𝟏𝟎 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟮: https://bit.ly/3yhEs7S
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About the Machine Learning with Python Training
Edureka’s Machine Learning Certification Training using Python is designed to make you grab the concepts of Machine Learning. This Machine Learning Certification will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in the python programming language. Furthermore, in this Machine Learning with Python Training, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of this Machine Learning online course, we will be discussing various practical use cases of Machine Learning with Python programming language to enhance your learning experience. Edureka offers the best Machine Learning Training online for those who want to be the best in Python. Enroll now with Edureka's online Machine Learning Certification to get trained with industrial experts.

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞 (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎) : https://www.edureka.co/advance....d-artificial-intelli
This Edureka LSTM Explained video will help you in understanding why we need Recurrent Neural Networks (RNN) and what exactly it is. It also explains few issues with training a Recurrent Neural Network and how to overcome those challenges using LSTMs.
00:00:00 Introduction
00:00:36 Agenda
00:00:47 Introduction to NLP
00:01:46 Ways to Process Text Data
00:02:57 Recurrent Neural Networks
00:22:02 Long Short-term Memory
00:51:46 LSTM Use Cases
00:53:45 Real Time Applications of LSTM

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Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

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In this video, we will explore the groundbreaking concept of Retrieval Augmented Generation (RAG), a revolutionary approach at the forefront of natural language processing (NLP). RAG represents a significant leap forward in text generation methodologies, seamlessly blending retrieval mechanisms with generative models to unlock new possibilities in AI-driven communication. Throughout this session, we will unravel the intricate workings of RAG, diving deep into its architecture, principles, and practical applications. We'll embark on a journey to understand how retrievers, acting as gateways to vast knowledge repositories, empower generative models to produce contextually rich and factually accurate text outputs. Join us as we navigate the landscape of RAG, exploring its potential to revolutionize various NLP tasks, from question answering to content generation. By the end of this video, you'll have a comprehensive understanding of RAG's transformative impact on natural language understanding and generation. So, without further ado, let's dive into the world of Retrieval Augmented Generation.

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➡️ About Post Graduate Program In AI And Machine Learning

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

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#ai #artificialintelligence #chatgpt #midjourney #llm #largelanguagemodels #largelanguagemodel

This is a short and very simple video I created to explain some of the concepts that go into large language models like Chat-GPT4. It covers various aspects of LLM artificial intelligence like foundations, architecture, pre-training, fine-tuning, tokenization, embeddings, self-attention, positional encoding, layers and headers, and decoding. The text was created with the use of chat gpt4. All of the images were created using Midjourney AI based on the text.

🔥Edureka Tensorflow Training: https://www.edureka.co/ai-deep....-learning-with-tenso
This Edureka LSTM Explained video will help you in understanding why we need Recurrent Neural Networks (RNN) and what exactly it is. It also explains few issues with training a Recurrent Neural Network and how to overcome those challenges using LSTMs.
00:00 Introduction
00:36 Agenda
00:47 Introduction to NLP
01:46 Ways to Process Text Data
02:57 Recurrent Neural Networks
22:02 Long Short-term Memory
51:46 LSTM Use Cases
53:45 Real Time Applications of LSTM

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🔹Check our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s

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#Edureka #DeepLearningEdureka #LSTMExplained #NeuralNetworks #DeepLearningTraining #DeepearningTutorial #EdurekaTraining

How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

- - - - - - - - - - - - - -

About the Course
Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.


- - - - - - - - - - - - - -

Who should go for this course?

The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'

2. Analytics Managers who are leading a team of analysts

3. Business Analysts who want to understand Deep Learning (ML) Techniques

4. Information Architects who want to gain expertise in Predictive Analytics

5. Professionals who want to captivate and analyze Big Data

6. Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.

- - - - - - - - - - - - - -

Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.


For more information, please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free).

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🔴 𝐋𝐞𝐚𝐫𝐧 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐅𝐨𝐫 𝐅𝐫𝐞𝐞! 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐂𝐡𝐚𝐧𝐧𝐞𝐥: https://edrk.in/DKQQ4Py

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www
.edureka.co/openai-chatgpt-training-course
This Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐫𝐚𝐬𝐡 𝐂𝐨𝐮𝐫𝐬𝐞 will explain what ChatGPT is all about. In this ChatGPT tutorial, you will learn about how ChatGPT works and the language model that ChatGPT uses.

ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large language models and has been fine-tuned using both supervised and reinforcement learning techniques.

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟒 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩ NEW Top 10 Technologies To Learn In 2024 - https://www.youtube.com/watch?v=vaLXPv0ewHU

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
In this Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥 𝐟𝐨𝐫 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫𝐬, you will learn how to use ChatGPT for coding and programming using different languages. ChatGPT can become a very. useful tool for every developer.
00:00:00 ChatGPT for Developers
00:00:40 What is ChatGPT
00:01:37 How ChatGPT Works
00:02:16 ChatGPT vs Codex
00:03:16 How to use ChatGPT
00:03:51 ChatGPT for Programming
00:04:06 ChatGPT for Shell Scripting
00:08:45 ChatGPT for Python Programming
00:10:47 ChatGPT for HTML and CSS Coding
00:12:10 ChatGPT for JavaScript

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
This Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 will talk about multiple use cases where you can use ChatGPT. There are several day to day applications where you can leverage ChatGPT to do the job for you. Below are some important ChatGPT applications covered in this ChatGPT tutorial:
00:00:00 Introduction
00:00:50 ChatGPT for Writing Code
00:02:25 ChatGPT for Code Debugging
00:03:37 ChatGPT for Content Writing
00:05:03 ChatGPT for SEO
00:06:18 ChatGPT for Language Translation
00:07:01 ChatGPT for Writing Legal Documents
00:08:11 ChatGPT for College Assignments
00:08:37 ChatGPT to make Workout Schedule

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In this comprehensive exploration of the field of deep learning with Professor Simon Prince who has just authored an entire text book on Deep Learning, we investigate the technical underpinnings that contribute to the field's unexpected success and confront the enduring conundrums that still perplex AI researchers.

Understanding Deep Learning - Prof. SIMON PRINCE [STAFF FAVOURITE]

Watch behind the scenes, get early access and join private Discord by supporting us on Patreon:
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https://twitter.com/MLStreetTalk

Key points discussed include the surprising efficiency of deep learning models, where high-dimensional loss functions are optimized in ways which defy traditional statistical expectations. Professor Prince provides an exposition on the choice of activation functions, architecture design considerations, and overparameterization. We scrutinize the generalization capabilities of neural networks, addressing the seeming paradox of well-performing overparameterized models. Professor Prince challenges popular misconceptions, shedding light on the manifold hypothesis and the role of data geometry in informing the training process. Professor Prince speaks about how layers within neural networks collaborate, recursively reconfiguring instance representations that contribute to both the stability of learning and the emergence of hierarchical feature representations. In addition to the primary discussion on technical elements and learning dynamics, the conversation briefly diverts to audit the implications of AI advancements with ethical concerns.

Pod version (with no music or sound effects): https://podcasters.spotify.com..../pod/show/machinelea

Follow Prof. Prince:
https://twitter.com/SimonPrinceAI
https://www.linkedin.com/in/si....mon-prince-615bb9165

Get the book now!
https://mitpress.mit.edu/97802....62048644/understandi
https://udlbook.github.io/udlbook/

Panel: Dr. Tim Scarfe -
https://www.linkedin.com/in/ecsquizor/
https://twitter.com/ecsquendor

TOC:
[00:00:00] Introduction
[00:11:03] General Book Discussion
[00:15:30] The Neural Metaphor
[00:17:56] Back to Book Discussion
[00:18:33] Emergence and the Mind
[00:29:10] Computation in Transformers
[00:31:12] Studio Interview with Prof. Simon Prince
[00:31:46] Why Deep Neural Networks Work: Spline Theory
[00:40:29] Overparameterization in Deep Learning
[00:43:42] Inductive Priors and the Manifold Hypothesis
[00:49:31] Universal Function Approximation and Deep Networks
[00:59:25] Training vs Inference: Model Bias
[01:03:43] Model Generalization Challenges
[01:11:47] Purple Segment: Unknown Topic
[01:12:45] Visualizations in Deep Learning
[01:18:03] Deep Learning Theories Overview
[01:24:29] Tricks in Neural Networks
[01:30:37] Critiques of ChatGPT
[01:42:45] Ethical Considerations in AI

References:

#61: Prof. YANN LECUN: Interpolation, Extrapolation and Linearisation (w/ Dr. Randall Balestriero)
https://youtube.com/watch?v=86ib0sfdFtw

Scaling down Deep Learning [Sam Greydanus]
https://arxiv.org/abs/2011.14439

"Broken Code" a book about Facebook's internal engineering and algorithmic governance [Jeff Horwitz]
https://www.penguinrandomhouse.....com/books/712678/br

Literature on neural tangent kernels as a lens into the training dynamics of neural networks.
https://en.wikipedia.org/wiki/....Neural_tangent_kerne

Zhang, C. et al. "Understanding deep learning requires rethinking generalization." ICLR, 2017.
https://arxiv.org/abs/1611.03530

Computer Vision: Models, Learning, and Inference, by Simon J.D. Prince
https://www.amazon.co.uk/Compu....ter-Vision-Models-Le

Deep Learning Book, by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
https://www.deeplearningbook.org/

Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network
https://arxiv.org/abs/2210.00881

Computer Vision: Algorithms and Applications, 2nd ed. [Szeliski]
https://szeliski.org/Book/

A Spline Theory of Deep Networks [Randall Balestriero]
https://proceedings.mlr.press/....v80/balestriero18b/b

DEEP NEURAL NETWORKS AS GAUSSIAN PROCESSES [Jaehoon Lee]
https://arxiv.org/abs/1711.00165

Do Transformer Modifications Transfer Across Implementations and Applications [Narang]
https://arxiv.org/abs/2102.11972

ConvNets Match Vision Transformers at Scale [Smith]
https://arxiv.org/abs/2310.16764

Dr Travis LaCroix (Wrote Ethics chapter with Simon)
https://travislacroix.github.io/

MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Amini
** New 2024 Edition **

For all lectures, slides, and lab materials: http://introtodeeplearning.com

Lecture Outline
0:00​ - Introduction
3:42​ - Sequence modeling
5:30​ - Neurons with recurrence
12:20 - Recurrent neural networks
14:08 - RNN intuition
17:14​ - Unfolding RNNs
19:54 - RNNs from scratch
22:41 - Design criteria for sequential modeling
24:24 - Word prediction example
31:50​ - Backpropagation through time
33:40 - Gradient issues
37:15​ - Long short term memory (LSTM)
40:00​ - RNN applications
44:00- Attention fundamentals
46:46 - Intuition of attention
49:13 - Attention and search relationship
51:22 - Learning attention with neural networks
57:45 - Scaling attention and applications
1:00:08 - Summary
Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!

🔥 Microsoft Power BI Certification Training: PwC Academy: https://www.edureka.co/power-b....i-certification-trai

This video on *Power BI Desktop* covers everything you need to know, from its evolution to practical applications. We'll dive into the history of Power BI, explaining what Power BI and Power BI Desktop are and why Power BI Desktop is a key tool for business intelligence. You'll also learn how to install Power BI Desktop, explore its features, and understand how to use it to create insightful reports. Finally, we'll guide you through the process of publishing a Power BI report. Whether you're a beginner or looking to expand your knowledge, this tutorial provides valuable insights into Power BI Desktop.

✅ 00:00 - Introduction to Power BI Desktop
✅ 01:08 - Evolution of Power BI
✅ 02:47 - What is Power BI?
✅ 03:22 - What is Power BI Desktop?
✅ 03:55 - Why is Power BI Desktop used?
✅ 04:28 - Power BI Desktop installation
✅ 05:04 - How is Power BI Desktop used?
✅ 17:09 - How to Publish Power BI Report?

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𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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About Power BI Certification Course

Edureka's Power BI certification course helps you master Business Analytics, covering Power BI Desktop, DAX, Service, Data Transformation, Reports, and more. With live instructor-led sessions and real-time projects, you’ll gain hands-on experience from industry experts with over 10 years of experience and be prepared to clear the PL-300 exam.
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What are the prerequisites for the Edureka Power BI training course?

There is no prior technical knowledge required for this Power BI training course. However, a fundamental understanding of Microsoft Excel, R and Python Scripts will be an advantage. To help you brush up concepts of R and Python Scripts, we will provide self-paced videos absolutely free in your LMS.
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Why should you learn Power BI course?

Power BI is a business analytics service provided by Microsoft. It provides interactive visualizations with self-service business intelligence capabilities, where end users can create reports and dashboards by themselves without having to depend on any information technology staff or database administrator. Microsoft Power BI Plus: Certified by PwC program shares knowledge on how it provides cloud-based BI services - known as Power BI Services, along with a desktop-based interface called Power BI Desktop. It offers Data modeling capabilities including data preparation, and data discovery, which can be utilized for implementing efficient interactive reports and dashboards.
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🔥Artificial Intelligence Engineer (IBM) - https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=zKrGRaQCWQE&utm_medium=DescriptionFirstFold&utm_source=Youtube
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In this Top 5 AI Technologies 2021 video, you will see the most popular AI technologies that are widely used. You will get a glance at these technologies and learn where artificial Intelligence can be used. You will get an idea of the different domains where AI has found its applications.


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#AITechnology #Top5AiTechnologies #TopArtificialIntelligenceTechnology #ArtificialIntelligenceApplications #Top5AITechnology #Simplilearn #Shorts

What is Artificial Intelligence?
Artificial Intelligence or AI is the combination of algorithms used for the purpose of creating intelligent machines that have the same skills as a human being. AI has made significant advances in the past few years and has impacted both our everyday lives and business in big ways. It is being widely used in every sector of business, such as Healthcare, E-Commerce, Manufacturing, Retail, and Logistics.

About Simplilearn Artificial Intelligence Course:
Simplilearn’s Artificial Intelligence course provides training in the skills required for a career in AI. You will master TensorFlow, Machine Learning and other AI concepts, plus the programming languages needed to design intelligent agents, deep learning algorithms & advanced artificial neural networks that use predictive analytics to solve real-time decision-making problems without explicit programming.

Why learn Artificial Intelligence?
The current and future demand for AI engineers is staggering. The New York Times reports a candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S. (or Rs.17 lakhs to Rs. 25 lakhs in India) for engineers with the required skills.

You can gain in-depth knowledge of Artificial Intelligence by taking our Artificial Intelligence certification training course. Those who complete the course will be able to:
1. Master the concepts of supervised and unsupervised learning
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3. Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning.
4. Understand the concepts and operation of support vector machines, kernel SVM, naive bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
5. Comprehend the theoretical concepts and how they relate to the practical aspects of machine learning.
6. Be able to model a wide variety of robust machine learning algorithms including deep learning, clustering, and recommendation systems

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