PyTorch- The Complete Guide 2022

PyTorch: The Complete Guide 2022, available at $54.99, has an average rating of 4.67, with 57 lectures, based on 3 reviews, and has 110 subscribers.

You will learn about Pandas Pytorch Numpy Artificial Neural Networks (ANN) Generative adversarial network (GAN) Convolution Neural Network (CNN) Recurrent Neural Network (RNN) Google Colab . Matplotlib. Long Short Term Memory (LSTM) Language Model Reinforcement Learning OpenAI Gym This course is ideal for individuals who are Anyone interested in Machine Learning. or Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence or Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning, Deep Learning, Artificial Intelligence. or Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets. or Any students in college who want to start a career in Data Science or Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence. or Any people who are not satisfied with their job and who want to become a Data Scientist. or Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer. or Any people who want to create added value to the local hospital by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. or Any people who want to work in healthcare field as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer. or Any people who want to work in a Taxi Company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer. It is particularly useful for Anyone interested in Machine Learning. or Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence or Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning, Deep Learning, Artificial Intelligence. or Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets. or Any students in college who want to start a career in Data Science or Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence. or Any people who are not satisfied with their job and who want to become a Data Scientist. or Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer. or Any people who want to create added value to the local hospital by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. or Any people who want to work in healthcare field as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer. or Any people who want to work in a Taxi Company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Enroll now: PyTorch: The Complete Guide 2022

Summary

Title: PyTorch: The Complete Guide 2022

Price: $54.99

Average Rating: 4.67

Number of Lectures: 57

Number of Published Lectures: 57

Number of Curriculum Items: 57

Number of Published Curriculum Objects: 57

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Pandas

Pytorch

Numpy

Artificial Neural Networks (ANN)

Generative adversarial network (GAN)

Convolution Neural Network (CNN)

Recurrent Neural Network (RNN)

Google Colab .

Matplotlib.

Long Short Term Memory (LSTM)

Language Model

Reinforcement Learning

OpenAI Gym

Who Should Attend

Anyone interested in Machine Learning.

Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence

Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning, Deep Learning, Artificial Intelligence.

Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets.

Any students in college who want to start a career in Data Science

Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.

Any people who are not satisfied with their job and who want to become a Data Scientist.

Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Any people who want to create added value to the local hospital by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools.

Any people who want to work in healthcare field as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Any people who want to work in a Taxi Company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Target Audiences

Anyone interested in Machine Learning.

Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence

Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning, Deep Learning, Artificial Intelligence.

Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets.

Any students in college who want to start a career in Data Science

Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.

Any people who are not satisfied with their job and who want to become a Data Scientist.

Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Any people who want to create added value to the local hospital by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools.

Any people who want to work in healthcare field as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Any people who want to work in a Taxi Company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Welcome to the best online course for learning about Pytorch!

Although Google’s Deep Learning library Tensorflow has gained massive popularity over the past few years, PyTorchhas been the library of choice for professionals and researchers around the globe for deep learning and artificial intelligence.

Is it possible that Tensorflow is popular only because Google is popular and used effective marketing?

Why did Tensorflow change so significantly between version 1 and version 2? Was there something deeply flawed with it, and are there still potential problems?

It is less well-known that PyTorch is backed by another Internet giant, Facebook (specifically, the Facebook AI Research Lab – FAIR). So if you want a popular deep learning library backed by billion dollar companies and lots of community support, you can’t go wrong with PyTorch. And maybe it’s a bonus that the library won’t completely ruin all your old code when it advances to the next version. 馃槈

On the flip side, it is very well-known that all the top AI shops (ex. OpenAI, Apple, and JPMorgan Chase) use PyTorch. OpenAI just recently switched to PyTorch in 2022, a strong sign that PyTorch is picking up steam.

In this course you will learn everything you need to know to get started with Pytorch, including:

NumPy

Pandas

Tensors with PyTorch

Neural Network Theory

Perceptrons

Networks

Activation Functions

Cost/Loss Functions

Backpropagation

Gradients

Artificial Neural Networks

Convolutional Neural Networks

Recurrent Neural Networks

and much more!

By the end of this course you will be able to create a wide variety of deep learning models to solve your own problems with your own data sets.

So what are you waiting for? Enroll today and experience the true capabilities of PyTorch! I’ll see you inside the course!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course structure

Lecture 2: How To Make The Most Out Of This Course

Lecture 3: Important note on tool

Lecture 4: What is neuron

Lecture 5: What is Multilayer Neural Network

Lecture 6: Simple Neural Network with Pytorch Implementation Part 1

Lecture 7: Simple Neural Network with Pytorch Implementation Part 2

Lecture 8: Simple Neural Network with Pytorch Implementation Part 3

Chapter 2: Image Processing with Pytorch

Lecture 1: More Explanation about CNN

Lecture 2: What is Convolution Neural Network?

Lecture 3: what is convolution layer

Lecture 4: what is pooling layer

Lecture 5: Project Time: MNIST Implementation Part 1: Importing libraries and data

Lecture 6: Project Time: MNIST Implementation Part 2

Lecture 7: Project Time: MNIST Implementation Part 3

Lecture 8: Project Time: MNIST Implementation Part 4

Lecture 9: Project Time: MNIST Implementation Part 5

Lecture 10: Project Time: MNIST Implementation Part 6

Chapter 3: GAN with Pytorch

Lecture 1: Introduction

Lecture 2: GAN Project: Importing libraries and data

Lecture 3: GAN Project: Generator Construction

Lecture 4: GAN Project: Discriminator Construction

Lecture 5: GAN Project: Defining optimizer and loss

Lecture 6: GAN Project: Fully Connected Network and results

Chapter 4: NLP with Pytorch

Lecture 1: Introduction to Recurrent Neural Network

Lecture 2: Recurrent Neural Network Implementation Part 1

Lecture 3: Recurrent Neural Network Part 1 Explanation

Lecture 4: Recurrent Neural Network Implementation Part 2

Lecture 5: Recurrent Neural Network Part 2 Explanation

Lecture 6: Introduction to Long short term Memory

Lecture 7: LSTMs Implementation Part 1

Lecture 8: LSTMs Implementation Part 1 Explanation and final implementation

Lecture 9: Language Model Implementation Part 1

Lecture 10: Language Model Implementation Part 1 (Explanation)

Lecture 11: Language Model Implementation Part 2 with detailed Explanation

Lecture 12: Language Model Implementation Part 3 with detailed Explanation

Lecture 13: Language Model Implementation final Part

Lecture 14: Language Model Implementation final Part (Explaination)

Chapter 5: Reinforcement with Pytorch

Lecture 1: What is Reinforcement Learning and Why we need Reinforcement Learning?

Lecture 2: Introduction to Reward

Lecture 3: Introduction to the agent, environment, action and observation

Lecture 4: How to set up the environment

Lecture 5: Introduction to OpenAI Gym

Lecture 6: Introduction to Robot Control and three laws of Robotics

Lecture 7: Short robotics timeline and Automatic control

Lecture 8: Reinforcement learning basics and Agent-environment interface

Lecture 9: Reinforcement Learning Algorithm

Lecture 10: Keras DQN

Lecture 11: Cart Pole Implementation Part 1

Lecture 12: Cart Pole Implementation Part 2

Lecture 13: Cart Pole Implementation Part 3

Lecture 14: Cart Pole Implementation Final Part

Lecture 15: Developing hill climbing part 1

Lecture 16: Developing hill climbing part 2

Lecture 17: Developing hill climbing part 3

Lecture 18: Developing hill climbing final Part

Chapter 6: Thank you

Lecture 1: Thank you

Instructors

Hoang Quy La
Electrical Engineer

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4 stars: 1 votes

5 stars: 2 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!