Books

Learn how to apply the Clean Architecture. The book strongly focuses on practical aspects and is illustrated with tons of code snippets. Code samples are in Python.

Teaser TextBuild smarter AI solutions for real-world problems.Volume 3 presents 10 intermediate-level AI projects covering intelligent tutoring, wildlife detection, healthcare scheduling, air-quality prediction, career recommendations, fire detection, adaptive e-learning, conversational AI, movie recommendations, and resume skill extraction.Each project follows the complete Software Development Life Cycle, helping readers move from problem identification and system design to AI development, testing, implementation, and future enhancement.Turn AI concepts into intelligent applications.

Mastering Deep Learning with PyTorch: From Fundamentals to Real-World Projects This first edition delivers a complete end-to-end learning pathway for mastering modern deep learning using PyTorch. Major Topics Covered • Deep Learning Fundamentals• Artificial Neural Networks• PyTorch Framework and Tensor Operations• Automatic Differentiation (Autograd)• Feedforward Neural Networks• Convolutional Neural Networks (CNNs)• Recurrent Neural Networks (RNNs)• Long Short-Term Memory Networks (LSTMs)• Attention Mechanisms• Transformer Architectures• Hugging Face Ecosystem• Generative Adversarial Networks (GANs)• Computer Vision Applications• Natural Language Processing Applications• Model Evaluation and Optimization• Hyperparameter Tuning• Explainable Artificial Intelligence (XAI)• Ethical AI and Bias Mitigation• Model Deployment and Production Pipelines Practical Implementations Included • Image Classification Systems• Object Detection Models• Image Segmentation Applications• Text Classification Systems• Sentiment Analysis Models• Language Translation Pipelines• Transformer-Based NLP Applications• GAN-Based Image Generation Capstone Projects Project 1: Pneumonia Detection using CNNProject 2: Sentiment Analysis using LSTMProject 3: Image Colorization using GANProject 4: Real-Time Object Detection SystemProject 5: Transformer-Based Intelligent Chatbot Industry Tools and Technologies • PyTorch• TorchVision• Hugging Face Transformers• TensorBoard• Flask• ONNX• Docker Concepts• AWS Deployment Basics• Google Cloud Deployment Concepts Intended Audience • Undergraduate Students• Postgraduate Students• Data Scientists• Machine Learning Engineers• AI Researchers• Software Developers• Academic Professionals• Industry Practitioners Learning Outcomes Upon completion of this book, readers will be able to:• Design and train neural network architectures.• Build computer vision applications using CNNs.• Develop NLP solutions using RNNs, LSTMs, and Transformers.• Implement generative AI systems using GANs.• Evaluate and optimize deep learning models.• Deploy PyTorch models into production environments.• Understand ethical considerations in AI development.• Create portfolio-ready deep learning projects.This release establishes a strong foundation for academic learning, industrial applications, and advanced research in modern deep learning.

Python 3 exercises for beginners. (English)Exercisis per a principiants. (Català)Ejercicios para principiantes. (Castellano)

Python 3 Combat Guide is a practical guide, full of actual experience and common sense, to avoid errors and to develop Python 3 Software Projects and System Administration programs.Targeted to SDM, Team Manager and Developers, defines practical strategies and tricks, and teach the basis of Unit Testing in pytest.You'll learn OOP easily.

Aprende todo sobre Python desde cero hasta experto. Curso para aprender Python paso a paso de forma fácil y con ejercicios prácticos que te ayuden a comprender todo sobre Python. El 100% del dinero recaudado con el libro será donado a @AmazonWatch, ONG que trabaja para proteger los bosques tropicales y los derechos de los pueblos indígenas.

What is a good software architecture? Why should we bother structuring the code and spending time testing it? If you like spending hours debugging your programs or staying late at the office to recover from a buggy deploy in production this book is definitely NOT for you!

A book designed to help you transition from merely knowing Python to cracking Leetcode patterns. This book explains core DSA concepts through clear, intuitive analogies and walks you through the most important Leetcode patterns. If you're aiming to ace your next coding interview, this is the book I wish I had when I started.

Master deep learning with PyTorch & Lightning. Core concepts, practical Q&A, and production-ready code with a full companion GitHub repository.

Ever wished someone would explain coding like they’re talking to a friend?That’s exactly what Python – Made Simpler does. This beginner-friendly book teaches Python with the help of real-life analogies you already understand. Variables become jars in your kitchen. Loops feel like chores on repeat. And instead of just reading about code, you’ll actually write it—from day one. You don’t need any prior experience. You don’t need to be a tech wizard. You just need curiosity—and maybe a little love for coffee, because we talk about that too. Start learning Python the fun way—with simplicity, creativity, and confidence.

Essential Python libraries and frameworks that every aspiring data scientist, ML engineer, and Python developer should know.

Quantitative finance in Python: a hands-on, interactive look at the QuantLib library through the use of Jupyter notebooks as working examples.

Ideas for projects when teaching Python as well as general inspiration ex. when building a hobby project. It sources use-cases from Reddit and is grouped in some 20 chapters.

A beginner-friendly introduction to machine learning with Python, that is based on the PyCaret and Streamlit libraries. Readers will delve into the fascinating world of artificial intelligence, by easily training and deploying their ML models!