Books

Learn how to implement various feature selection methods in a few lines of code and train faster, simpler, and more reliable machine learning models. Using Python open-source libraries, you will learn how to find the most predictive features from your data through filter, wrapper, embedded, and additional feature selection methods.

This is a short manual to understand the 4th Industrial Revolution Technologies & 5G in very easy & understandable language.

Recently, convolutional neural networks have surpassed humans in different tasks such as classification of natural objects and classification of traffic signs. After their great success, convolutional neural networks have become the first choice for learning features from training data.

This is a short manual to understand the 4th Industrial Revolution Technologies in very easy & understandable language.

IF your data isn't contextual, connected, complete & controllable; you don't control your data, your talent, and the impact they can make; you don't know how to use data to manage the cycle of innovation in a global market; you're not in the Sweet Spot where this comes together in harmony... This is the book you didn't even know you needed

Hiring Data Scientists and Machine Learning Engineers is a concise, practical guide to help you hire the right people for your organization. The book will help you navigate the plethora of data science related roles and skills and help you create an effective hiring strategy to suit your organization's needs.

This series will introduce you to the Python programming language. It’s aimed at beginning programmers, but even if you’ve written programs before and just want to add Python to your list of languages, Introducing Python will get you started.

Recently, researchers have found a theory that explains every aspect of conscious experience. This book explores this theory and introduces you to neuroscience and gives you instructions how to build a conscious machine.

Are you interested in learning about graph theory and applied network analysis, leveraging your Python skills? Then this is the book for you! See how network science & graph theory connects with a variety of data analysis problems, and use it to solve your next data science challenge!

G>G>G> 研究、生活、幸福。G>G>

Aprende los conceptos básicos del Machine Learning y avanza poco a poco con teoría y divertidos ejercicios prácticos en Python a niveles intermedios y avanzados hasta llegar al Deep Learning.Tu camino para convertirte en un Científico de Datos comienza aquí

Isn't it weird that ML software is super important, yet crazy fragile? If ML software is valuable but so unstable, how come data scientists and ML engineers are rarely trained on the basics of building profitable software systems? What to do about it?

Revised for PyTorch 2.x! In 2019, I published a PyTorch tutorial on Towards Data Science and I was amazed by the reaction from the readers! Their feedback motivated me to write this book to help beginners start their journey into Deep Learning and PyTorch. I hope you enjoy reading this book as much as I enjoy writing it.

Focus on building working solutions

Have you ever been curious about how your phone unlocks when it sees your face, how a camera can track people and objects in a video, how humans see depth, or how computers can differentiate dogs from cats? This book will start from the basics of image manipulation and build up to cover all of these topics, and more!