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๐ฅ ๐๐๐ฎ๐ซ๐๐ค๐ ๐๐๐ ๐๐๐ซ๐ญ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง ๐๐ซ๐๐ข๐ง๐ข๐ง๐ ๐ฐ๐ข๐ญ๐ก ๐๐ฒ๐ญ๐ก๐จ๐ง : https://www.edureka.co/python-....natural-language-pro (๐๐ฌ๐ ๐๐จ๐๐: ๐๐๐๐๐๐๐๐๐)
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.
0:00 Introduction
2:42 Why Mathematics in Machine Learning?
5:03 Linear Algebra - Scalars
6:20 Linear Algebra - Vectors
7:14 Linear Algebra - Vector Operations
11:22 Linear Algebra - Matrices
13:48 Linear Algebra - Matrix Operations
20:25 Linear Algebra - Vector as Matrix
22:35 Linear Algebra โ Vector as Matrix
26:10 Linear Algebra - Eigen Vectors
27:42 Linear Algebra - Applications
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About Course :
About the Natural Language Processing with Python course
Edureka's Natural Language Processing Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. This NLP course has been packed up with a lot of real-life examples, where you can apply the learned content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics, and Machine Learning have been discussed as a part of this NLP training. This NLP course is for anyone who works with data and textโ with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of this NLP Certification course, we will be discussing various practical use cases of NLP in the python programming language to enhance your learning experience.
๐ฅ Edureka Machine Learning Certification training (๐๐ฌ๐ ๐๐จ๐๐: ๐๐๐๐๐๐๐๐๐) : https://www.edureka.co/masters....-program/machine-lea
This Edureka video on 'Support Vector Machine Tutorial For Beginners' covers A brief introduction to Support Vector Machine in Python with a use case to implement SVM using Python.
Topics covered in this video:
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About the Course :
Edurekaโs 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.
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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.
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Who should go for this Course?
Edurekaโs Python Machine Learning Certification Course is a good fit for the below professionals:
Developers aspiring to be a โMachine 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
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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 [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
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This Edureka Live tutorial on โAWS Machine Learning Tutorialโ will introduce you to the nitty-gritty of Cloud Computing, Machine Learning and help you build an ML model using AWS.
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How it Works?
1. This is a 5 Week Instructor led Online Course.
2. The 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!
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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, a 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
Who should go for this course?
This course is designed for students and IT professionals who want to pursue a career in Cloud Computing. The course is the best fit for:
1. Professionals interested in managing highly-available and fault-tolerant enterprise and web-scale software deployments.
2. Professionals who want Project Experience in migrating and deploying cloud-based solutions.
3. DevOps professionals.
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.
For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).