Udemy – PyTorch for Deep Learning with Python Bootcamp 2019-9

Udemy – PyTorch for Deep Learning with Python Bootcamp 2019-9 Downloadly IRSpace

Apr 16, 2025 - 20:48 Updated: Apr 20, 2025 - 11:12

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Udemy – PyTorch for Deep Learning with Python Bootcamp 2019-9

PyTorch for Deep Learning with Python Bootcamp is a video tutorial on the PyTorch library from Udemy. PyTorch is an open-source deep learning platform that provides a seamless path from research prototyping to production deployment. It is fast becoming one of Python\’s most popular deep learning frameworks. Deep integration in Python allows popular libraries and packages to be used to easily write neural network layers in Python.

This course focuses on balancing important concepts of theory with practical exercises and projects that will teach you how to incorporate the concepts in the course into your dataset.

Feature of the PyTorch course for Deep Learning with Python Bootcamp

Learn the classic principles of machine learning theory
Develop deep learning models for working with tabular data
Learn how to use NumPy to format data in an array
Learn how to use the pandas library to manipulate and clear data
Using PyTorch with recursive neural network for time series data
Tutorial Using the PyTorch Deep Learning Library for Image Classification

Course specifications

English language
Duration: 17:00:56
Number of lessons: 97
Tutor: Jose Portilla
File format: mp4

Course headings

Course Overview, Installs, and Setup
2 lectures 25:02

COURSE OVERVIEW CONFIRMATION CHECK
0 lectures 00:00

Crash Course: NumPy
7 lectures 46:23

Crash Course: Pandas
9 lectures 01:13:19

PyTorch Basics
7 lectures 54:32

Machine Learning Concepts Overview
6 lectures 46:57

ANN – Artificial Neural Networks
22 lectures 04:44:09

CNN – Convolutional Neural Networks
22 lectures 04:21:05

Recurrent Neural Networks
12 lectures 02:10:20

Using a GPU with PyTorch and CUDA
2 lectures 30:47

NLP with PyTorch
7 lectures 01:08:14

BONUS SECTION: THANK YOU!
1 lecture 00:11

Course prerequisites

Understanding of Python Basic Topics (data types, loops, functions) is also recommended by Python OOP
Be able to work through basic derivative calculations
Admin Permissions on your computer (ability to download our files)