Data

Cut through the noise and get real results with a step-by-step approach to learning SQL

Cut through the noise and get real results with a step-by-step approach to data science

Unleash the power of Python libraries like Gensim, NLTK, SpaCy, and Keras to solve common and not-so-common challenges faced in the NLP domain.

Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning.

Master the capabilities of PostgreSQL 12 such as advanced indexing, high availability, database configuration, database monitoring, and more to efficiently manage and maintain your database

Take your enterprise application development skills to the next level by mastering parallel programming techniques in .NET and C#.

Build powerful deep learning models using fewer learning samples with the power of scikit-learn and Keras

Increase the performance of various neural network architectures using NEAT, HyperNEAT, ES-HyperNEAT, Novelty Search, SAFE, and Deep Neuroevolution.

Learn the essential background and model functioning of various neural network architectures such as CNN. RNN. LSTM, GANs, Autoencoders and more using best practices from an industry expert

Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network models

Build powerful artificial intelligent applications using Hyperledger, Ethereum, Corda, Chain Core, Quorum, IOTA and more

Real world financial applications with AI and production-grade data feed/technology

A new edition of the bestselling guide to Deep Reinforcement Learning and how it can be used to solve complex real-world problems. Revised and expanded to include multi-agent methods, discrete optimization, RL in robotics, advanced exploration techniques, and more

Build machine and deep learning systems with the newly released TensorFlow 2.0 and Keras for the lab, production, and mobile devices

Build and train neural network models with high speed and flexibility in text, vision, and advanced analytics using PyTorch 1.x