Are you ready to go on a journey into the world of deep learning? This course will be your guide through the joys and dangers of this new wave of machine learning. Why? Because, let’s face it, getting started with deep learning is difficult. Tasks such as choosing between multiple frameworks, understanding APIs, and debugging code are hard. Is there an another way? Yes. Meet PyTorch. Like Python, PyTorch has a clean and simple API, which makes building neural networks faster and easier. It’s also modular, and that makes debugging your code a breeze. This course will be one hell of an adventure into the world of deep learning!
You’ll start by using Convolutional Neural Networks (CNNs) to classify images; Recurrent Neural Networks (RNNs) to detect languages; and then translate them using Long–Term–Short Memory (LTSM). Finally, you’ll channel your inner Picasso by using Deep Neural Network (DNN) to paint unique images.
By the end of your adventure, you will be ready to use PyTorch proficiently in your real–world projects.
About the Author
Jakub Konczyk has enjoyed programming professionally since 1995. He is a Python and Django expert and has been involved in building complex systems since 2006. He loves to simplify and teach programming subjects and share them with others. He first discovered Machine Learning when he was trying to predict real estate prices in one of the early stage startups he was involved in. He failed miserably. Then he discovered a much more practical way to learn Machine Learning, which he would like to share with you in this course. It boils down to the Keep it simple! mantra.
Specification: Deep Learning Adventures with PyTorch