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Design and develop high-performance programs in Julia 1.0Key FeaturesLearn the characteristics of high-performance Julia codeUse the power of the GPU to write efficient numerical …
Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of …
Publisher's Note: A new edition of this book is out now that includes working with GPT-3 and comparing the results with other models. It includes even more use cases, such as …
Learn to build expert NLP and machine learning projects using NLTK and other Python libraries About This Book * Break text down into its component parts for spelling correction, …
Foster your NLP applications with the help of deep learning, NLTK, and TensorFlowKey FeaturesWeave neural networks into linguistic applications across various platformsPerform NLP …
Make NLP easy by building chatbots and models, and executing various NLP tasks to gain data-driven insights from raw text dataKey FeaturesGet familiar with key natural language …
Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems.Key FeaturesAssimilate key NLP concepts and terminologies …
Use Java and Deeplearning4j to build robust, scalable, and highly accurate AI models from scratchKey FeaturesInstall and configure Deeplearning4j to implement deep learning models …
One-stop solution for NLP practitioners, ML developers, and data scientists to build effective NLP systems that can perform real-world complicated tasksKey FeaturesApply deep …
Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutionsKey FeaturesBecome well-versed with KNIME Analytics …