Machine Learning in 30 Days: The Complete Beginner’s Guide is the ultimate step-by-step roadmap for anyone looking to master machine learning with Python from scratch. Designed to take you from a complete beginner to a confident ML practitioner in just 30 days, this book provides a structured, easy-to-follow approach to learning machine learning Python efficiently.
With hands-on exercises, real-world projects, and expert explanations, this book is perfect for students, professionals, and hobbyists who want a machine learning for dummies style guide without compromising depth. Whether you're curious about why machine learning is essential today, or you're eager to dive into deep learning with Python, this book will guide you through everything you need to know.What You’ll Learn in 30 Days
✔ The fundamentals of machine learning, including supervised and unsupervised learning✔ How to preprocess data, handle missing values, and perform feature engineering✔ Implementing popular ML algorithms, including linear regression, decision trees, SVMs, and KNN✔ Advanced concepts, including neural networks, CNNs for image recognition, and RNNs for time-series forecasting✔ Deep learning with Python using TensorFlow and Keras✔ Deploying machine learning models with Flask, FastAPI, and cloud platforms✔ Building real-world ML projects, such as fraud detection, recommendation systems, and sentiment analysisWhy