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Learn the fundamentals of statistics and machine learning using R libraries for data processing, visualization, model training, and statistical inference Key Features Advance your …
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 …
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 …
Elevate your machine learning skills using the Conformal Prediction framework for uncertainty quantification. Dive into unique strategies, overcome real-world challenges, and …
Master effective navigation of neural networks, including convolutions and transformers, to tackle computer vision and NLP tasks using Python Key Features Understand the theory, …
Build advanced NLU systems by utilizing NLP libraries such as NLTK, SpaCy, BERT, and OpenAI; ML libraries like Keras, scikit-learn, pandas, TensorFlow, and NumPy, along with …
An in-depth analysis into the world of deep learning using Apache MXNet for flexible and efficient research prototyping and deployment to production Key Features A step-by-step …
Kickstart your emotion analysis journey with this step-by-step guide to data science success Key Features Discover the inner workings of the end-to-end emotional analysis workflow …
Harness ChatGPT for streamlined flows, effective configuration, proficient code writing, and enhanced project activities Key Features Boost your processes for improved quality and …