Learn IT - Books tags learning

Machine Learning and Robot Perception (Studies in Computational Intelligence)

Springer, 2005

This book presents some of the most recent research results in the area of machine learning and robot perception. The book contains eight chapters.

Relevant progress has been done, within the Robotics field, in mechanical systems, actuators, control and planning. This fact, allows a wide application of industrial robots, where...

Deep Learning with PyTorch: A practical approach to building neural network models using PyTorch

Packt Publishing, 2018

Build neural network models in text, vision and advanced analytics using PyTorch

Key Features

Learn PyTorch for implementing cutting-edge deep learning algorithms.

Train your neural networks for higher speed and flexibility and learn how to implement them in various...

Intelligent Autonomous Systems: Foundations and Applications

Springer, 2010

Intelligent Autonomous Systems (IAS) are the physical embodiment of machine intelligence providing a core concept for integrating various advanced technologies with pattern recognition and learning. The basic philosophy of IAS research is to explore and understand the nature of intelligence in problems of perception, reasoning, learning and...

Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Packt Publishing, 2019

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

Build a strong foundation in neural networks and deep learning with Python libraries

Explore advanced deep learning techniques and their applications...

Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python

Packt Publishing, 2018

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras

Key Features

Implement machine learning algorithms to build, train, and validate algorithmic models

Create your own algorithmic design process to apply...

Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7

Packt Publishing, 2019

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality.

Key Features

Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and...

fastText Quick Start Guide: Get started with Facebook's library for text representation and classification

Packt Publishing, 2018

Perform efficient fast text representation and classification with Facebook's fastText library

Key Features

Introduction to Facebook's fastText library for NLP

Perform efficient word representations, sentence classification, vector representation

Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more

Packt Publishing, 2021

Take your NLP knowledge to the next level and become an AI language understanding expert by mastering the quantum leap of Transformer neural network models

Key Features

Build and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using...

Python Data Analytics: With Pandas, NumPy, and Matplotlib

Apress, 2018

Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.

This revision is fully updated with new content on social media data analysis, image...

Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Packt Publishing, 2018

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems.

Key Features

Explore deep reinforcement learning (RL), from the first principles to the latest algorithms

Evaluate high-profile RL methods, including value...

Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch

Apress, 2021

Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by...

PyTorch Recipes: A Problem-Solution Approach

Apress, 2019

Get up to speed with the deep learning concepts of Pytorch using a problem-solution approach. Starting with an introduction to PyTorch, you'll get familiarized with tensors, a type of data structure used to calculate arithmetic operations and also learn how they operate. You will then take a look...

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