Video: .MP4, AVC, 1280×720, 30 fps | Audio: English, AAC, 44.1 KHz, 2 Ch | Duration: 3h 15m | 5.31 GBInstructor: Minerva SinghHands-on PyTorch boot camp for Artificial Intelligence applications with artificial neural networks and deep learningKey FeaturesA full introduction to Python Data Science and Anaconda, a powerful Python-driven data science frameworkA thorough grounding in how to use PyTorch to implement common deep learning algorithms such as Convolutional Neural Networks (CNNs) on real-life dataLimited mathematical jargon. The course focuses on teaching people basic Python data science concepts and builds up to using PyTorchWhat You Will LearnDeep Learning Basics – Getting started with Anaconda, an important Python data science environmentNeural Network Python Applications – Configuring the Anaconda environment to get started with PyTorchIntroduction to Deep Learning Neural Networks – Theoretical underpinnings of important concepts (such as deep learning) without the jargonAI Neural Networks – Implementing Artificial Neural Networks (ANNs) with PyTorchNeural Network Model – Implementing deep learning (DL) models with PyTorchDeep Learning AI – Implement common machine learning algorithms for image classificationDeep Learning Neural Networks – Implement PyTorch-based deep learning algorithms on image dataAboutMaster the latest and hottest deep learning frameworks (PyTorch) for Python data scienceThis course is your complete guide to practical machine learning and deep learning using the PyTorch framework in Python and covers the important aspects of PyTorch.

If you take this course, you’ll have no need to take other courses or buy 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; the advent of frameworks such as PyTorch is revolutionizing deep learning.

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

After taking this course, you’ll be able to use packages such as Numpy, Pandas, and PIL to work with real data in Python and you’ll be fluent in PyTorch. We even introduce you to deep learning models such as Convolution Neural Networks (CNNs)!The underlying motivation for the course is to ensure you can apply Python-based data science on real data today, start analyzing data for your own projects whatever your skill level, and impress potential employers with actual examples of your data science abilities.

All the codes and supporting files for this course are available at – github.com/PacktPublishing/PyTorch-Bootcamp-for-Artificial-Neural-Networks-and-Deep-Learning-Applications