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Building data fabric eliminates the technological complexities of data governance so users can connect to the right data at the right time, regardless of where it resides, automate the enforcement of data protection policies, and activate metadata to build data products faster for more intelligent decisions. Scott Buckles quickly explains this topic in 5 minutes.

Create Data Fabric instead of Data Silos: https://ibm.biz/Governance_and_Data_Fabric
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#AI #Software #ITModernization #DataGovernance #lightboard #IBM #watsonx

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🔥Edureka Deep Learning Training - TensorFlow Certification:- https://www.edureka.co/ai-deep....-learning-with-tenso
This Edureka video on the "GPT-3 Explained" will help you understand why and what is GPT 3 Language Model, followed by its Use cases and limitations. Following Pointers are covered in this GPT-3 explained video:
00:00:00 Introduction
00:00:57 Introduction to GPT
00:02:50 Practical Applications of GPT Deep Learning Model
00:04:54 Datasets and Parameters used in GPT 3
00:06:44 Limitations of GPT Algorithm
00:08:14 How you can use GPT

🔹Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
🔹Check our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s
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#Edureka #EdurekaTensorFlow #GPT3 #Tensorflowtutorial #tensorflow2.0 #TensorFlowTraining #Edureka #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.

For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
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.

⏩ Edureka ChatGPT Explained Playlist: http://bit.ly/3HGRy3G

#ChatGPTCrashCourse #edureka #chatgptexplained #chatgpt #openai #chatgpttutorial #chatgpt3 #ai #nlp #artificialintelligence

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
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🔵 Artificial and Machine Learning PGD with E&ICT Academy
NIT Warangal: http://bit.ly/3OuZ3xs

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⏩ NEW Top 10 Technologies To Learn In 2023 - https://youtu.be/udD_GQVDt5g

🔵 About Edureka ChatGPT Certification Training Course

Edureka’s ChatGPT Certification Training Course will teach you about ChatGPT architecture, GPT models, methodology, and real-world applications. The ChatGPT certification training program is an excellent choice for individuals and organizations seeking to improve their language processing and AI skills and knowledge.

🔵 Why take up the Online ChatGPT Certification Course?

Interested individuals can opt for the Online ChatGPT Certification course as this course provides:

Comprehensive knowledge: The course provides a comprehensive understanding of ChatGPT, including its architecture, training methodology, and real-world applications.

Career advancement: The certification demonstrates an individual's expertise and competence in working with ChatGPT, making them a valuable asset to any organization.

Stay ahead of the curve: ChatGPT is a rapidly growing field, and with the certification, one can stay ahead of the curve and stay updated with the latest advancements in the industry.

Enhance skills: The course provides practical skills and knowledge that can be applied to various areas and industries.

🔵 Who should take up this ChatGPT Certification Course?

The ChatGPT Certification Course is suitable for a wide range of individuals, including:

AI professionals: This course is ideal for AI professionals who want to gain expertise in ChatGPT and expand their knowledge in the field of AI.

Developers: Developers who want to integrate ChatGPT into their projects and create new AI applications can benefit from the course.

Data scientists: Data scientists who want to understand how ChatGPT can be used to process and analyze large amounts of data can also benefit from the course.

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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.

🔥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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📝Feel free to share your comments below.📝

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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🔵 Angular Online Training: http://bit.ly/3EYcCTe

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
🌕 Cloud Architect Masters Program: http://bit.ly/3OvueZy
🔵 Data Scientist Masters Program: http://bit.ly/3tUAOiT
🌕 Big Data Architect Masters Program: http://bit.ly/3tTWT0V
🔵 Machine Learning Engineer Masters Program: http://bit.ly/3AEq4c4
🌕 Business Intelligence Masters Program: http://bit.ly/3UZPqJz
🔵 Python Developer Masters Program: http://bit.ly/3EV6kDv
🌕 RPA Developer Masters Program: http://bit.ly/3OteYfP
🔵 Web Development Masters Program: http://bit.ly/3U9R5va
🌕 Computer Science Bootcamp Program : http://bit.ly/3UZxPBy
🔵 Cyber Security Masters Program: http://bit.ly/3U25rNR
🌕 Full Stack Developer Masters Program : http://bit.ly/3tWCE2S
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🌕 Python Developer Masters Program : https://bit.ly/3EV6kDv
🔵 Azure Cloud Engineer Masters Program: http://bit.ly/3AEBHzH

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬

🌕 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3Ov52lT

🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh


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📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

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

🔥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

​Want to learn Microsoft Azure ASAP? Batch Starting Soon for Microsoft Azure. ENROLL NOW!! Click here to get started : https://bit.ly/3j7KaCi

🔥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

🔴 Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

📝Feel free to share your comments below.📝

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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🔵 React Online Training: http://bit.ly/3Vc4yDw
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🔵 Power BI Online Training: http://bit.ly/3VntjMY
🌕 Selenium Online Training: http://bit.ly/3EVDtis
🔵 PMP Online Training: http://bit.ly/3XugO44
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🔵 Cybersecurity Online Training: http://bit.ly/3tXgw8t
🌕 Java Online Training: http://bit.ly/3tRxghg
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🌕 CEHv12 Online Training: http://bit.ly/3Vhq8Hj
🔵 Angular Online Training: http://bit.ly/3EYcCTe

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
🌕 Cloud Architect Masters Program: http://bit.ly/3OvueZy
🔵 Data Scientist Masters Program: http://bit.ly/3tUAOiT
🌕 Big Data Architect Masters Program: http://bit.ly/3tTWT0V
🔵 Machine Learning Engineer Masters Program: http://bit.ly/3AEq4c4
🌕 Business Intelligence Masters Program: http://bit.ly/3UZPqJz
🔵 Python Developer Masters Program: http://bit.ly/3EV6kDv
🌕 RPA Developer Masters Program: http://bit.ly/3OteYfP
🔵 Web Development Masters Program: http://bit.ly/3U9R5va
🌕 Computer Science Bootcamp Program : http://bit.ly/3UZxPBy
🔵 Cyber Security Masters Program: http://bit.ly/3U25rNR
🌕 Full Stack Developer Masters Program : http://bit.ly/3tWCE2S
🔵 Automation Testing Engineer Masters Program : http://bit.ly/3AGXg2J
🌕 Python Developer Masters Program : https://bit.ly/3EV6kDv
🔵 Azure Cloud Engineer Masters Program: http://bit.ly/3AEBHzH

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🌕 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3Ov52lT

🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh


📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
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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.
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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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➡️ About Caltech Post Graduate Program In AI And Machine Learning

Designed to boost your career as an AI and ML professional, this program showcases Caltech CTME's excellence and IBM's industry prowess. The artificial intelligence course covers key concepts like Statistics, Data Science with Python, Machine Learning, Deep Learning, NLP, and Reinforcement Learning through an interactive learning model with live sessions.

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El Machine Learning y el Deep Learning son clave para la evolución de la Inteligencia Artificial porque permiten que las máquinas puedan aprender y mejorar por sí mismas, logrando que estas máquinas puedan hacer tareas complejas y resolver problemas de manera autónoma. Pero, ¿qué es Machine Learning y Deep Learning exactamente? Te lo explicaremos en este nuevo video de EDteam.

Y si no lo sabías #LoAprendisteEnEDteam

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1. Curso: Android desde cero https://edy.to/android-yt
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Si quieres que EDteam de una conferencia gratis en tu institución, contáctanos aquí 👉 https://ed.team/conferencias

💻 Cursos recomendados:
- Carrera: Machine Learning e Inteligencia Artificial https://ed.team/especialidades/machine-learning
- Curso: Introducción al Machine Learning https://edy.to/ML-yt
- Curso: Introducción a las redes neuronales artificiales https://edy.to/redes-neuronales-yt
- Curso: Redes neuronales con TensorFlow https://edy.to/tensorflow-yt


📺 Videos recomendados
- ¿Qué es la Inteligencia Artificial y cómo está cambiando al mundo? https://www.youtube.com/watch?v=98-SzelNMzU
- ¿Qué es el Big Data? https://www.youtube.com/watch?v=M26iIqmqWkI&t=6s
- ¡Los peores errores de programación de la historia! https://www.youtube.com/watch?v=qi9nFs2caj4

⌚ Timeline:
00:00 - Introducción
00:59 - Que es Machine Learning
04:50 - Tipos de MAchine Learning
08:00 - Las Redes Neuronales
11:40 - El Deep Learning


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Prepare for a job interview about deep learning. This course covers 50 common interview questions related to deep learning and gives detailed explanations.

✏️ Course created by Tatev Karen Aslanyan.

✏️ Expanded course with 100 questions: https://academy.lunartech.ai/p....roduct/deep-learning

⭐️ Contents ⭐️
⌨️ 0:00:00 Introduction
⌨️ 0:08:20 Question 1: What is Deep Learning?
⌨️ 0:11:45 Question 2: How does Deep Learning differ from traditional Machine Learning?
⌨️ 0:15:25 Question 3: What is a Neural Network?
⌨️ 0:21:40 Question 4: Explain the concept of a neuron in Deep Learning
⌨️ 0:24:35 Question 5: Explain architecture of Neural Networks in simple way
⌨️ 0:31:45 Question 6: What is an activation function in a Neural Network?
⌨️ 0:35:00 Question 7: Name few popular activation functions and describe them
⌨️ 0:47:40 Question 8: What happens if you do not use any activation functions in a neural network?
⌨️ 0:48:20 Question 9: Describe how training of basic Neural Networks works
⌨️ 0:53:45 Question 10: What is Gradient Descent?
⌨️ 1:03:50 Question 11: What is the function of an optimizer in Deep Learning?
⌨️ 1:09:25 Question 12: What is backpropagation, and why is it important in Deep Learning?
⌨️ 1:17:25 Question 13: How is backpropagation different from gradient descent?
⌨️ 1:19:55 Question 14: Describe what Vanishing Gradient Problem is and it’s impact on NN
⌨️ 1:25:55 Question 15: Describe what Exploding Gradients Problem is and it’s impact on NN
⌨️ 1:33:55 Question 16: There is a neuron in the hidden layer that always results in an error. What could be the reason?
⌨️ 1:37:50 Question 17: What do you understand by a computational graph?
⌨️ 1:43:28 Question 18: What is Loss Function and what are various Loss functions used in Deep Learning?
⌨️ 1:47:15 Question 19: What is Cross Entropy loss function and how is it called in industry?
⌨️ 1:50:18 Question 20: Why is Cross-entropy preferred as the cost function for multi-class classification problems?
⌨️ 1:53:10 Question 21: What is SGD and why it’s used in training Neural Networks?
⌨️ 1:58:24 Question 22: Why does stochastic gradient descent oscillate towards local minima?
⌨️ 2:03:38 Question 23: How is GD different from SGD?
⌨️ 2:08:19 Question 24: How can optimization methods like gradient descent be improved? What is the role of the momentum term?
⌨️ 2:14:22 Question 25: Compare batch gradient descent, minibatch gradient descent, and stochastic gradient descent.
⌨️ 2:19:12 Question 26: How to decide batch size in deep learning (considering both too small and too large sizes)?
⌨️ 2:26:01 Question 27: Batch Size vs Model Performance: How does the batch size impact the performance of a deep learning model?
⌨️ 2:29:33 Question 28: What is Hessian, and how can it be used for faster training? What are its disadvantages?
⌨️ 2:34:12 Question 29: What is RMSProp and how does it work?
⌨️ 2:38:43 Question 30: Discuss the concept of an adaptive learning rate. Describe adaptive learning methods
⌨️ 2:43:34 Question 31: What is Adam and why is it used most of the time in NNs?
⌨️ 2:49:59 Question 32: What is AdamW and why it’s preferred over Adam?
⌨️ 2:54:50 Question 33: What is Batch Normalization and why it’s used in NN?
⌨️ 3:03:19 Question 34: What is Layer Normalization, and why it’s used in NN?
⌨️ 3:06:20 Question 35: What are Residual Connections and their function in NN?
⌨️ 3:15:05 Question 36: What is Gradient clipping and their impact on NN?
⌨️ 3:18:09 Question 37: What is Xavier Initialization and why it’s used in NN?
⌨️ 3:22:13 Question 38: What are different ways to solve Vanishing gradients?
⌨️ 3:25:25 Question 39: What are ways to solve Exploding Gradients?
⌨️ 3:26:42 Question 40: What happens if the Neural Network is suffering from Overfitting relate to large weights?
⌨️ 3:29:18 Question 41: What is Dropout and how does it work?
⌨️ 3:33:59 Question 42: How does Dropout prevent overfitting in NN?
⌨️ 3:35:06 Question 43: Is Dropout like Random Forest?
⌨️ 3:39:21 Question 44: What is the impact of Drop Out on the training vs testing?
⌨️ 3:41:20 Question 45: What are L2/L1 Regularizations and how do they prevent overfitting in NN?
⌨️ 3:44:39 Question 46: What is the difference between L1 and L2 regularisations in NN?
⌨️ 3:48:43 Question 47: How do L1 vs L2 Regularization impact the Weights in a NN?
⌨️ 3:51:56 Question 48: What is the curse of dimensionality in ML or AI?
⌨️ 3:53:04 Question 49: How deep learning models tackle the curse of dimensionality?
⌨️ 3:56:47 Question 50: What are Generative Models, give examples?

This video is about the Fast Fourier Transform.

This is the third in a series of videos about Fourier transforms.

- First video: The Discrete Fourier Transform https://www.youtube.com/watch?v=T8XZxR5H04E
- Second video: Detecting Periodicity with the DFT https://youtu.be/bk9VGJNzQM0
- Third video: The Fast Fourier Transform (this one)

Grokking Machine Learning Book:
https://www.manning.com/books/....grokking-machine-lea
40% discount promo code: serranoyt

00:00 Introduction
00:27 The Discrete Fourier Transform
03:01 The Fast Fourier Transform
07:28 The Butterfly

Latent Dirichlet Allocation is a powerful machine learning technique used to sort documents by topic. Learn all about it in this video!

This is part 1 of a 2 video series.
Video 2: https://www.youtube.com/watch?v=BaM1uiCpj_E

For information on my book "Grokking Machine Learning": https://www.manning.com/books/....grokking-machine-lea
Discount code (40%): serranoyt

0:00 Introduction
0:11 The problem
3:47 Machine that generates documents
5:13 Blueprint for the LDA machine
5:49 Probability of a document
9:22 Quiz: Which one for topics?
11:06 A distribution of distributions
11:30 More topics? More dimensions
12:20 In More dimensions
12:55 Quiz: Where to put the topics?
14:05 Two Dirichlet distributions
14:22 Latent Dirichlet Allocation
22:05 Best settings on the machine
22:37 The winning arrangements
25:28 Series of two videos
25:48 Acknowledgements
26:30 Thank you!

Highlight: At 33:30 Josh Starmer, Statsquatch, and the Normalsaurus from @statquest have an awesome cameo!

A video about autoencoders, a very powerful generative model. The video includes:
Intro: (0:25)
Dimensionality reduction (3:35)
Denoising autoencoders (10:50)
Variational autoencoders (18:15)
Training autoencoders (23:36)

Github repo: www.github.com/luisguiserrano/autoencoders

Recommended videos:
Generative adversarial networks: https://www.youtube.com/watch?v=8L11aMN5KY8
Restricted Boltzmann machines: https://www.youtube.com/watch?v=Fkw0_aAtwIw
Matrix factorization: https://www.youtube.com/watch?v=ZspR5PZemcs
Singular value decomposition: https://www.youtube.com/watch?v=DG7YTlGnCEo
Neural networks: https://www.youtube.com/watch?v=BR9h47Jtqyw
Convolutional neural networks: https://www.youtube.com/watch?v=2-Ol7ZB0MmU
Recurrent neural networks: https://www.youtube.com/watch?v=2-Ol7ZB0MmU
Logistic regression: https://www.youtube.com/watch?v=jbluHIgBmBo
Shannon entropy: https://www.youtube.com/watch?v=9r7FIXEAGvs

Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

0:00 Introduction
0:13 Generative models
3:03 Variational autoencoders
3:45 Dataset of images
10:16 Denoising autoencoders
10:27 Linear methods
10:53 A friendly introduction to deep learning and neural networks
11:58 Mapping the real numbers to the interval (0,1)
12:23 Sigmoid function
12:41 Perceptron
15:02 Correct noise
18:20 Autoencoders as generators
20:16 Latent space
23:41 Training a neural network - loss function
25:18 Training an autoencoder
25:32 Training autoencoders
25:46 Reconstruction loss (Mean squared error)
26:31 Reconstruction loss (log-loss)
27:11 Training a variational auto encoder

Correction: At 30:05, the number in the middle of the red graph should be 0.4, not 0.3.

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% Discount code: serranoyt

Welcome! I believe that math concepts can be learned through simple explanations, analogies and easy-to-understand visualizations. I am passionate about teaching math concepts in relatable, friendly and simple ways. My videos are designed so that beginners can clearly learn new concepts while experts can see them under a new light. I hope you enjoy the channel and please drop me a line if you have any comments or suggestions. Twitter: @luis_likes_math.