Showing results for "jayakumar singaram"
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Deep Learning Networks
Design, Development and Deployment
2023
EN
Accessible
This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners. It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a practical way to understand the relationships between programming and technology for a variety of applications. It offers a tutorial for the reader to learn wide-r...
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- From Scratch
2024
EN
How to implement LLM attention mechanisms and GPT-style transformers.In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.Build a Large Language Model (from Scratch) t...
2021
EN
Unlock the groundbreaking advances of deep learning with this extensively revised edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world.In Deep Learning with Python, Second Edition you will learn:Deep learning from first principlesImage classification & image segmentationTimeseries forecastingText classification...
Building AI Agents with LLMs, RAG, and Knowledge Graphs
A practical guide to autonomous and modern AI agents
2025
EN
Master LLM fundamentals to advanced techniques like RAG, reinforcement learning, and knowledge graphs to build, deploy, and scale intelligent AI agents that reason, retrieve, and act autonomously DRM-free PDF version + access to Packt's next-gen ReaderKey FeaturesImplement RAG and knowledge graphs for advanced problem-solvingLeverage innovative approaches like LangChain to create real-world intelligent systemsIntegrate large language models, gr...
Generative AI with Python and TensorFlow 2
Create images, text, and music with VAEs, GANs, LSTMs, Transformer models
2021
EN
This edition is heavily outdated and we have a new edition with PyTorch examples published!Key FeaturesCode examples are in TensorFlow 2, which make it easy for PyTorch users to follow alongLook inside the most famous deep generative models, from GPT to MuseGANLearn to build and adapt your own models in TensorFlow 2.xExplore exciting, cutting-edge use cases for deep generative AIBook DescriptionMachines are excelling...
Deep Learning with TensorFlow and Keras
Build and deploy supervised, unsupervised, deep, and reinforcement learning models, 3rd Edition
2022
EN
Build cutting edge machine and deep learning systems for the lab, production, and mobile devices.Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesImplement graph neural networks, transformers using Hugging Face and TensorFlow Hub, and joint and contrastive learni...
Deep Learning with TensorFlow 2 and Keras
Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API
2019
EN
Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devicesKey FeaturesIntroduces and then uses TensorFlow 2 and Keras right from the startTeaches key machine and deep learning techniquesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesBook DescriptionDeep Learning with TensorFlow 2 and ...
Hands-On Computer Vision with TensorFlow 2
Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras
2019
EN
A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and moreKey FeaturesDiscover how to build, train, and serve your own deep neural networks with TensorFlow 2 and KerasApply modern solutions to a wide range of applications such as object detection and video analysisLearn how to run your models on mobile devices and web pages and improve their performance
2022
EN
Your secret weapon to understanding—and using!—one of the most powerful influences in the world todayFrom your Facebook News Feed to your most recent insurance premiums—even making toast!—algorithms play a role in virtually everything that happens in modern society and in your personal life. And while they can seem complicated from a distance, the reality is that, with a little help, anyone can understand—and even use—these powerful problem-solving tools!In...
Ultimate Neural Network Programming with Python
Create Powerful Modern AI Systems by Harnessing Neural Networks with Python, Keras, and TensorFlow
2023
EN
Master Neural Networks for Building Modern AI Systems.DESCRIPTIONThis book is a practical guide to the world of Artificial Intelligence (AI), unraveling the math and principles behind applications like Google Maps and Amazon. The book starts with an introduction to Python and AI, demystifies complex AI math, teaches you to implement AI concepts, and explores high-level AI libraries.Throughout the chapters, readers are engaged with th...
Mastering PyTorch
Build powerful neural network architectures using advanced PyTorch 1.x features
2021
EN
Master advanced techniques and algorithms for deep learning with PyTorch using real-world examplesKey FeaturesUnderstand how to use PyTorch 1.x to build advanced neural network modelsLearn to perform a wide range of tasks by implementing deep learning algorithms and techniquesGain expertise in domains such as computer vision, NLP, Deep RL, Explainable AI, and much moreBook DescriptionDeep learning is driving the AI revolution...
Practical Machine Learning for Computer Vision
End-to-End Machine Learning for Images
2021
EN
This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretabi...











