Udemy – PyTorch: Deep Learning and Artificial Intelligence 2020-6

Description

PyTorch: Deep Learning and Artificial Intelligence is the name of a course on the Udemy site that introduces you to the PyTorch library and explains the topic of neural networks for computer vision, time series prediction, NLP, booster learning, GAN, and more. . PyTorch is an open source machine learning library developed by Facebook AI Research Lab and used for applications such as computer vision and natural language processing.

Although Google's Tensorflow Deep Learning Library has become very popular over the past few years, the PyTorch Library is also the first choice of many experts in deep learning and artificial intelligence. Creating and testing new ideas with PyTorch is much easier than other libraries, and it is easy to work on popular projects in this library. During this course, you will become fully acquainted with PyTorch and design various projects with its help.

Items that are taught in this course

Training of artificial networks and deep neural networks

Stock price forecast

Time series forecast

Computer vision

Build a robot to learn stock trading

GAN

Torsional neural network

PyTorch course specifications: Deep Learning and Artificial Intelligence

English language

Duration: 22 hours and 42 minutes

Number of courses: 140

Level of education: Intermediate

Instructor: Lazy Programmer Team, Lazy Programmer Inc

File format: mp4

Topics

140 lectures 22:42:15

Introduction 3 lectures 22:53

Google Colab 3 lectures 34:57

Machine Learning and Neurons 15 lectures 02:32:29

Feedforward Artificial Neural Networks 9 lectures 01:49:01

Convolutional Neural Networks 13 lectures 02:22:13

Recurrent Neural Networks, Time Series, and Sequence Data 17 lectures 03:05:32

Natural Language Processing (NLP) 9 lectures 01:23:44

Recommender Systems 5 lectures 46:18

Transfer Learning for Computer Vision 6 lectures 41:35

GANs (Generative Adversarial Networks) 3 lectures 31:42

Deep Reinforcement Learning (Theory) 14 lectures 02:21:10

Stock Trading Project with Deep Reinforcement Learning 9 lectures 01:07:08

VIP: Uncertainty Estimation 2 lectures 16:48

VIP: Facial Recognition 10 lectures 55:18

In-Depth: Loss Functions 3 lectures 23:15

In-Depth: Gradient Descent 5 lectures 41:41

Extras 2 lectures 00:27

Setting up your Environment 3 lectures 01:00:05

Appendix / FAQ 9 lectures 01:45:58

Prerequisite

Know how to code in Python and Numpy

For the theoretical parts (optional), understand derivatives and probability

Installation

After Extract, watch with your favorite Player.

English subtitle

Quality: 720p