Get Sht Done With Pytorch Solve Realworld Machine Learning Problems With Deep Neural Networks In Python Venelin Valkov by Venelin Valkov instant download after payment.

Learn how to solve real-world problems with Deep Learning models (NLP, Computer Vision, and Time Series). Go from prototyping to deployment with PyTorch and Python!
PyTorch is the best Deep Learning library there (currently) is, period! Doing ML with PyTorch feels like a superpower (of course, there are bad parts, too). Trust me, I have a book on TensorFlow and Keras! This opinion comes from my real-world experience, as a Machine Learning Engineer, and writer of numerous Machine Learning and Deep Learning tutorials.
This book skips the bull and goes straight into solving real-world problems. There is some theory, only where you need to connect the dots. You'll go from the basics of using PyTorch to solving Computer Vision, Natural Language, and Time Series problems with complete source code and runnable Jupyter notebooks.
In my humble opinion, PyTorch is the sweet way to solve Machine Learning problems, in the real world! The vast community allows you to work state-of-the-art models and deploy them to production in no time (relatively speaking).
The examples are compatible with the latest versions of PyTorch and Torchvision.
Here’s what you’ll learn from this book:
■Getting Started with PyTorch
■Build Your First Neural Network with PyTorch
■Transfer Learning for Image Classification using Torchvision
■Time Series Forecasting with LSTMs for Daily Coronavirus Cases
■Time Series Anomaly Detection using LSTM Autoencoders
■Face Detection on Custom Dataset with Detectron2
■Create Dataset for Sentiment Analysis by Scraping Google Play App Reviews
■Sentiment Analysis with BERT and Transformers by Hugging Face
■Deploy BERT for Sentiment Analysis as REST API using FastAPI