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PyTorch Tutorial - Neural Networks & Deep Learning in Python

Pytorch - Introduction to deep learning neural networks : Neural network applications tutorial : AI neural network model

4.59 (76 reviews)


6 hours


Mar 2020

Last Update
Regular Price

What you will learn

Deep Learning Basics - Getting started with Anaconda, an important Python data science environment

Neural Network Python Applications - Configuring the Anaconda environment for getting started with PyTorch

Introduction to Deep Learning Neural Networks - Theoretical underpinnings of the important concepts (such as deep learning) without the jargon

AI Neural Networks - Implementing artificial neural networks (ANN) with PyTorch

Neural Network Model - Implementing deep learning (DL) models with PyTorch

Deep Learning AI - Implement common machine learning algorithms for Image Classification

Deep Learning Neural Networks - Implement PyTorch based deep learning algorithms on imagery data


Master the Latest and Hottest of Deep Learning Frameworks (PyTorch)  for Python Data Science


It is a full 5-Hour+ PyTorch Boot Camp that will help you learn basic machine learning, neural networks and deep learning  using one of the most important Python Deep Learning frameworks- PyTorch.                         


This course is your complete guide to practical machine & deep learning using the PyTorch framework in Python..

This means, this course covers the important aspects of PyTorch and if you take this course, you can do away with taking other courses or buying books on PyTorch.  

In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and advent of frameworks such as PyTorch is revolutionizing Deep Learning...

By gaining proficiency in PyTorch, you can give your company a competitive edge and boost your career to the next level.


But first things first. My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real life data from different sources  using data science related techniques and producing publications for international peer reviewed journals.

 Over the course of my research I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic and use data science interchangeably with machine learning..

This gives students an incomplete knowledge of the subject. My course, on the other hand, will give you a robust grounding in all aspects of data science within the PyTorch framework.

Unlike other Python courses and books, you will actually learn to use PyTorch on real data!  Most of the other resources I encountered showed how to use PyTorch on in-built datasets which have limited use.


• A full introduction to Python Data Science and powerful Python driven framework for data science, Anaconda
• Getting started with Jupyter notebooks for implementing data science techniques in Python
• A comprehensive presentation about PyTorch installation and a brief introduction to the other Python data science packages
• A brief introduction to the working of important data science packages such as Pandas and Numpy
• The basics of the PyTorch syntax and tensors
• The basics of working with imagery data in Python
• The theory behind neural network concepts such as artificial neural networks, deep neural networks and convolutional neural networks (CNN)
• You’ll even discover how to create artificial neural networks and deep learning structures with PyTorch (on real data)


You’ll start by absorbing the most valuable PyTorch basics and techniques.

I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts.

My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Python-based data science in real -life.

After taking this course, you’ll easily use packages like Numpy, Pandas, and PIL to work with real data in Python along with gaining fluency in PyTorch. I will even introduce you to deep learning models such as Convolution Neural network (CNN) !!

The underlying motivation for the course is to ensure you can apply Python-based data science on real data into practice today, start analyzing data for your own projects whatever your skill level, and impress your potential employers with actual examples of your data science abilities.

It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, the majority of the course will focus on implementing different techniques on real data and interpret the results. Some of the problems we will solve include identifying credit card fraud and classifying the images of different fruits.

After each video, you will learn a new concept or technique which you may apply to your own projects!


#deep #learning #neural #networks #python #ai #programming


PyTorch Tutorial - Neural Networks & Deep Learning in Python
PyTorch Tutorial - Neural Networks & Deep Learning in Python
PyTorch Tutorial - Neural Networks & Deep Learning in Python
PyTorch Tutorial - Neural Networks & Deep Learning in Python


Introduction To the Course - Welcome to the PyTorch Primer

Welcome to PyTorch

Data and Scripts

Get Started With the Python Data Science Environment: Anaconda

Anaconda for Mac Users

The iPython Environment

Why PyTorch?

Install PyTorch

Installing PyTorch-Written Instructions

Further Installation Instructions for Mac

Working With CoLabs

Introduction to Python Data Science Packages (Other Than PyTorch)

Python Packages for Data Science

Introduction to Numpy

Create Numpy Arrays

Numpy Operations

Numpy for Basic Vector Arithmetric

Numpy for Basic Matrix Arithmetic

PyTorch Basics: What Is a Tensor?

Explore PyTorch Tensors and Numpy Arrays

Some Basic PyTorch Tensor Operations

Other Python Data Science Packages For Dealing With Data

Read in CSV data

Read in Excel data

Basic Data Exploration With Pandas

Basic Statistical Analysis With PyTorch

Ordinary Least Squares (OLS) Regression- Theory

OLS Linear Regression-Without PyTorch

OLS Linear Regression From First Principles-Theory

OLS Linear Regression From First Principles-Without PyTorch

OLS Linear Regression From First Principles-With PyTorch

More OLS With PyTorch

Generalised Linear Models (GLMs)-Theory

Logistic Regression-Without PyTorch

Logistic Regression-With PyTorch

Introduction to Artificial Neural Networks (ANN)

Introduction to ANN

PyTorch ANN Syntax

What Are Activation Functions? Theory

More on Backpropagation

Bringing Them Together

Setting Up ANN Analysis With PyTorch

DNN Analysis with PyTorch

More DNNs

DNNs For Identifying Credit Card Fraud

An Explanation of Accuracy Metrics

Neural Networks on Images

What Are Images?

Read in Images in Python

Basic Image Conversions

Why AI and Deep Learning?

Artificial Neural Networks (ANN) For Image Classification

Deep Neural Networks (DNN) For Image Classification

Introduction to Artificial Intelligence (AI) and Deep Learning

What is CNN?

Implement CNN on Imagery Data

Implement CNN Using a Pre-Trained Model


Rishilal22 August 2021

This is an amazing course with high value contents. The concept has vast opportunities for practical applications. the course is ideally suited for my work. The instructor's lectures in the course are simply brilliant.

Waylon10 August 2021

The instructor explains the code implementation very poorly. She just read off the codes and didn't explain why.

Rajesh2 August 2021

The course contains finer technical details of the concept having significant value and the same have been brilliantly explained by the instructor in her crisp lectures. The course is very much relevant and useful for my work and I will be able to make use of it gainfully.

RKM25 July 2021

This is a hands-on course for me . Many of the issues which I am dealing with have got clarified through lectures of this course. The instructor has clarity of thought and has explained the concepts in the course in an unambiguous manner.

John30 June 2021

the course works for me but the image quality of lecture 25 was awful. I think you could also show more of the code as you are explaining since I typed the code into PyCharm to work alongside

Bryan3 March 2021

Overall, this was a good intro to PyTorch and some of its uses. I have much more experience with TensorFlow which helped. I liked how the beginning started off with working with the tensors first and then doing regression using PyTorch as a way to help understand the framework. The repetition of the last few sections is helpful in getting the structure of the framework material to sink in.

Jagjit23 February 2021

The course content is good but the delivery is not great. Lot of concepts and code are not explained properly. I had to watch youtube videos and read articles on medium to understand the concepts.

Ramesh12 November 2020

The course contains very useful information. Tailor-made for my purpose. The instructor has latest update about the course.

Anonymized13 September 2020

It,s amazing. The course content is of very high class and the lectures have been perfectly designed and ideally arranged. Very enriching experience.

C21 May 2020

Lots to cover, some of the content should be split from the course when talking about theory, where as the execution of ANN and CNN is the focus of the course. More examples of CNN would be greatly appreciated.

Lisa5 February 2020

It is brief and easy to understand. if you don't like to hear a lot about theories, this might be a good course for you.

Marcelo2 February 2020

The course goes too fast without explaining the essentials of Pytorch nor critical APIs. Moreover, two lectures go over TenfoFlow and Keras code!! The tutorials over the internet (free of charge) explain much better the concepts and building blocks of (deep) neural networks than this course.

Jojo31 August 2019

Very intense. I had to brush up my programming skills beforehand but its has robust material on pyTroch

Quentin22 August 2019

Not suitable for people who don't have programming knowledge. But it provides a good basis for working with PyTorch. Its fast

Viva22 August 2019

It is not suitable for beginners who don't have a programming background. But it covers PyTorch very well


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3/9/2021100% OFFExpired


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