Feature Engineering & Selection for Explainable Models

by Md Azimul Haque

FBT review:

Unlock the secrets of building impactful machine learning models with "Feature Engineering & Selection for Explainable Models" by Md Azimul Haque. Dive deep into the world of explainable AI, feature engineering, and selection techniques that will elevate your data science skills. Learn metaheuristic algorithms, leverage open-source tools in Python, and tackle real-world challenges with four diverse datasets. Communicate results clearly and future-proof your skills in the competitive AI landscape. Whether you're a budding data scientist, experienced ML engineer, or a student aiming for the top, this book is your key to success. Take your skills to the next level and become the data scientist who builds models that excel in both performance and explainability. Purchase your copy today and master the art of machine learning.

Publisher Description:

Master the Art of Feature Engineering, Feature Selection, and Explainable AI to Unlock the True Mark of a Great Data Scientist, and Machine Learning Engineer. Bridge the Gap Between Raw Data and Actionable Insights With This Book That Shows You How!Struggling to build machine learning models that truly deliver? Ready to go beyond basic techniques and develop Explainable AI models, which are impactful, and job-ready? This is the course your career needs.In the age of black-box algorithms, feature engineering and feature selection is your secret weapon to build models that not only perform better but also explain why they work. This book takes you beyond the basics, diving deep into the real-world challenges of machine learning. With practical guidance, cutting-edge algorithms, and custom developed Python libraries, this is the only resource you’ll need to elevate your data science game.Whether you’re a budding data scientist, an experienced machine learning engineer, or a student aiming for the top, this book delivers tailored benefits:Build Better Models: Learn metaheuristic algorithms like genetic algorithms, simulated annealing, particle swarm optimization, and ant colony optimization to perform feature selection with precision.Leverage Open-Source Tools: Master the art of feature engineering and signal processing, all in Python, with open-source libraries developed exclusively for this book.Solve Real Problems: Go beyond toy datasets and experience the full journey of machine learning model development with four real-world datasets, tackling challenges every data scientist faces.Communicate Results Clearly: Learn to justify outcomes with data and facts, even when models fail to meet expectations.Future-Proof Your Skills: Gain practical expertise to deliver models that excel in both performance and explainability, setting yourself apart in the competitive world of AI.And more!Ready to become the data scientist who builds Explainable AI models that succeed in the real world?Get your copy of "Feature Engineering & Selection for Explainable Models" and take your skills to the next level today!Scroll up, Click on “Buy Now”, and Grab Your Copy Today!