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Enhance your writing with AI by mastering prompt engineering techniques and become an expert in developing and utilizing LLM prompts across applications Key Features Master prompt …
A deep and detailed dive into the key aspects and challenges of machine learning interpretability, complete with the know-how on how to overcome and leverage them to build fairer, …
Demystify causal inference and casual discovery by uncovering causal principles and merging them with powerful machine learning algorithms for observational and experimental data …
Explore the vast possibilities of integrating the ChatGPT API across various domains, from creating simple wrappers to developing knowledge-based assistants, multi-model …
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 …
Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer …
New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, …
Over 70 recipes to help you develop smart applications on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano using the power of machine learning …
Comprehensive recipes to give you valuable insights on Transformers, Reinforcement Learning, and moreKey FeaturesDeep Learning solutions from Kaggle Masters and Google Developer …
Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystemKey …