Mastering Scikit Learn
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Mastering Machine Learning With Scikit Learn Second Edition
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Author : Gavin Hackeling
language : en
Publisher:
Release Date : 2017-07-27
Mastering Machine Learning With Scikit Learn Second Edition written by Gavin Hackeling and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-27 with Computers categories.
Mastering Machine Learning With Scikit Learn
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Author : Gavin Hackeling
language : en
Publisher:
Release Date : 2014-10-29
Mastering Machine Learning With Scikit Learn written by Gavin Hackeling and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-29 with Machine learning categories.
If you are a software developer who wants to learn how machine learning models work and how to apply them effectively, this book is for you. Familiarity with machine learning fundamentals and Python will be helpful, but is not essential.
Mastering Scikit Learn
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Author : GILBERT. GUTIERREZ
language : en
Publisher: Independently Published
Release Date : 2025-02-05
Mastering Scikit Learn written by GILBERT. GUTIERREZ and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-05 with Computers categories.
AI from Scratch: Step-by-Step Guide to Mastering Artificial Intelligence - Book 5 Unlock the power of machine learning with Scikit-Learn, Python's most popular ML library! Whether you're a beginner looking to understand the basics or a professional aiming to refine your skills, Mastering Scikit-Learn: Practical ML for Everyone is your ultimate guide to building, optimizing, and deploying machine learning models effectively. This book is the fifth installment in the AI from Scratch series, designed to provide a structured, hands-on approach to mastering artificial intelligence. With real-world case studies, step-by-step tutorials, and best practices, you'll gain the confidence to apply machine learning to real business and research problems. What You'll Learn: Part 1: Getting Started with Scikit-Learn Introduction to machine learning and the Scikit-Learn ecosystem Setting up your Python environment and loading datasets Data preprocessing: handling missing values, feature scaling, and encoding categorical variables Part 2: Core Machine Learning Models Implementing linear regression, logistic regression, and decision trees Building powerful ensemble models like Random Forest and Gradient Boosting Understanding Support Vector Machines (SVMs) and clustering techniques (K-Means, DBSCAN, PCA) Part 3: Advanced Techniques & Optimization Feature engineering and recursive feature elimination Hyperparameter tuning with GridSearchCV and Bayesian optimization Handling imbalanced data, anomaly detection, and data augmentation Automating ML workflows with Pipelines and AutoML Part 4: Real-World Applications & Deployment End-to-end machine learning project case studies Integrating Scikit-Learn with TensorFlow and PyTorch Deploying ML models using Flask, FastAPI, and cloud platforms Avoiding common pitfalls and optimizing model performance Who Should Read This Book? Beginners & Students - Learn machine learning from the ground up with hands-on coding examples. Data Scientists & ML Engineers - Deepen your understanding of model tuning and feature engineering. Software Developers - Implement Scikit-Learn models into real-world applications. Business Analysts & AI Enthusiasts - Discover how ML models can drive data-driven decisions. Why Choose This Book? Step-by-Step Learning - Practical examples and code snippets guide you through each concept. Real-World Case Studies - Apply machine learning to real datasets and projects. Hands-on Approach - Learn by doing with interactive exercises and Python implementations. Industry Best Practices - Avoid common pitfalls and optimize your ML models for accuracy and efficiency. Part of the AI from Scratch Series - A structured learning path from beginner to AI mastery. Start Your Machine Learning Journey Today! Whether you're exploring machine learning for the first time or looking to enhance your skills, Mastering Scikit-Learn provides the tools, techniques, and knowledge you need to succeed. Take the next step in your AI journey-Master Scikit-Learn and build powerful machine learning models today!
Scikit Learn Essentials
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Author : Dhiraj Kumar
language : en
Publisher:
Release Date : 2019
Scikit Learn Essentials written by Dhiraj Kumar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
"Master scikit-learn through a combination of lecture and hands-on (via Jupyter) in this eight-part video series: Scikit-learn Overview; Installing Scikit-learn; Loading Data Sets using Scikit-learn; Pre-processing Data using Scikit-learn; Splitting Data into Train Sets and Test Sets in Scikit-learn; Linear Regression using Scikit-learn; Naïve Bayes using Scikit-learn; SVM using Scikit-learn."--Resource description page.
Mastering Scikit Learn And Machine Learning
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Author : Ed Norex
language : en
Publisher: Independently Published
Release Date : 2024-02-28
Mastering Scikit Learn And Machine Learning written by Ed Norex and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-28 with Computers categories.
"Mastering Scikit-Learn and Machine Learning" is the definitive guide for anyone aiming to harness the full potential of one of the most powerful and widely used machine learning libraries in the Python ecosystem. Whether you're a beginner taking your first step into the world of machine learning, or an experienced practitioner seeking to deepen your understanding and expand your toolkit, this book offers a comprehensive exploration of Scikit-Learn's capabilities. Structured into ten detailed chapters, "Mastering Scikit-Learn and Machine Learning" meticulously covers every aspect of machine learning. From getting started with the basics, through data preprocessing, supervised and unsupervised learning, to advanced model tuning and customization, this book ensures a thorough grounding as well as providing cutting-edge techniques. Each chapter is designed to build on the knowledge of the previous one, introducing complex concepts in an accessible manner and providing practical examples that bridge the gap between theory and application. Readers will learn to navigate the challenges of data preprocessing, utilize various regression and classification algorithms, understand the power of unsupervised learning, and implement ensemble learning techniques to improve model performance. Additionally, the book delves into working with text data, evaluating and selecting models, reducing dimensionality, and leveraging advanced tuning for finely tuned custom models. "Mastering Scikit-Learn and Machine Learning" is not just a book but a valuable resource filled with insights, best practices, and practical examples. It is an essential companion for data scientists, machine learning engineers, analysts, and anyone passionate about unlocking the potential of data through machine learning. Embark on a journey to mastering Scikit-Learn and empower yourself to tackle real-world problems with confidence and proficiency.
Mastering Scikit Learn
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Author : Ravindra Kumar Nayak
language : en
Publisher: Independently Published
Release Date : 2023-11-28
Mastering Scikit Learn written by Ravindra Kumar Nayak and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-28 with categories.
"Embark on a captivating journey through the realm of machine learning with an innovative blend of storytelling and technical exploration in our book on scikit-learn. Unveiling characters like Decision Trees and SVMs, each chapter weaves an engaging narrative, introducing concepts, and providing hands-on examples. Readers navigate preprocessing, model crafting, and validation, experiencing the power of algorithms like Random Forests and Neural Networks. The book concludes with insights into model evaluation and deployment. This unique approach combines education with entertainment, ensuring an enjoyable and insightful odyssey for those venturing into the fascinating world of scikit-learn."
Mastering Pandas
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Author : Ashish Kumar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-10-25
Mastering Pandas written by Ashish Kumar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-25 with Computers categories.
Perform advanced data manipulation tasks using pandas and become an expert data analyst. Key FeaturesManipulate and analyze your data expertly using the power of pandasWork with missing data and time series data and become a true pandas expertIncludes expert tips and techniques on making your data analysis tasks easierBook Description pandas is a popular Python library used by data scientists and analysts worldwide to manipulate and analyze their data. This book presents useful data manipulation techniques in pandas to perform complex data analysis in various domains. An update to our highly successful previous edition with new features, examples, updated code, and more, this book is an in-depth guide to get the most out of pandas for data analysis. Designed for both intermediate users as well as seasoned practitioners, you will learn advanced data manipulation techniques, such as multi-indexing, modifying data structures, and sampling your data, which allow for powerful analysis and help you gain accurate insights from it. With the help of this book, you will apply pandas to different domains, such as Bayesian statistics, predictive analytics, and time series analysis using an example-based approach. And not just that; you will also learn how to prepare powerful, interactive business reports in pandas using the Jupyter notebook. By the end of this book, you will learn how to perform efficient data analysis using pandas on complex data, and become an expert data analyst or data scientist in the process. What you will learnSpeed up your data analysis by importing data into pandasKeep relevant data points by selecting subsets of your dataCreate a high-quality dataset by cleaning data and fixing missing valuesCompute actionable analytics with grouping and aggregation in pandasMaster time series data analysis in pandasMake powerful reports in pandas using Jupyter notebooksWho this book is for This book is for data scientists, analysts and Python developers who wish to explore advanced data analysis and scientific computing techniques using pandas. Some fundamental understanding of Python programming and familiarity with the basic data analysis concepts is all you need to get started with this book.
Learn Scikit Learn
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Author : Studiod21 Smart Tech Content
language : en
Publisher: Independently Published
Release Date : 2025-04-25
Learn Scikit Learn written by Studiod21 Smart Tech Content and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-25 with Computers categories.
LEARN Scikit-Learn: Essential Machine Learning for Data Science This book is the key to mastering Scikit-Learn and building market-ready Machine Learning projects. Ideal for professionals and students who seek fast, direct, and applicable results. Learn high-impact techniques, design intelligent solutions, and boost your career in data science. Includes: - Quick setup of a productive environment with Python and Scikit-Learn - Data preprocessing and full pipeline automation - Fine-tuning models with cross-validation and hyperparameters - Practical application of regression, classification, and clustering - Model deployment integrated with Big Data and MLOps environments Master the most widely used algorithms in the market and accelerate your entry into data science projects with Scikit-Learn. scikit-learn, machine learning, data science, smart pipelines, model automation, cross-validation, machine learning deployment, big data integration, mlops, spark
100 Steps To Learn Ai A Journey From Curiosity To Mastery
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Author : Dr. Gurram Veera Raghavaiah
language : en
Publisher: Dr. Gurram Veera Raghavaiah
Release Date : 2025-12-27
100 Steps To Learn Ai A Journey From Curiosity To Mastery written by Dr. Gurram Veera Raghavaiah and has been published by Dr. Gurram Veera Raghavaiah this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-27 with Antiques & Collectibles categories.
This book offers a transformative 100-step roadmap to holistic AI mastery across six phases, blending technical skills, ethics, and stewardship. Prologue: Awakening (Steps 1-5) begins with "What is intelligence?", contextualizing AI/ML/DL in daily life and inspiring vision. Phase I: Foundation (6-20) builds Python fluency with NumPy, Pandas, Matplotlib; revives Linear Algebra, Stats, Calculus as model language; sets up environments, version control, first predictive program, and early ethics. Phase II: ML Engine (21-40) covers supervised/unsupervised/RL algorithms (regression, KNN, trees, SVMs, clustering), Scikit-learn workflows, metrics (accuracy, F1, RMSE), bias-variance tradeoff, and end-to-end projects. Phase III: Deep Dive (41-60) explores perceptrons to backprop, TensorFlow/PyTorch, CNNs/RNNs/LSTMs, Dropout/Transfer Learning, GANs/VAEs, and NLP basics. Phase IV: Frontier (61-80) introduces Transformers/Hugging Face, RL (Q-Learning/DQNs), Docker/cloud deployment, Kaggle/ArXiv engagement, and portfolio building. Phase V: Integration (81-95) specializes in Vision/NLP/RL, masters MLOps, XAI (SHAP/LIME), bias/fairness, interdisciplinary fusion, and communication/mentoring for T-shaped professionals. Phase VI: Ascent (96-100) demands novel projects, open sharing, and "nurture the garden" stewardship. This narrative expedition cultivates wise practitioners to integrate AI responsibly into society
Mastering Machine Learning With Python And Scikit Learn
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Author : Katarina Juric
language : en
Publisher: Independently Published
Release Date : 2025-04-14
Mastering Machine Learning With Python And Scikit Learn written by Katarina Juric and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-14 with Computers categories.
Unlock the power of machine learning with Mastering Machine Learning with Python and Scikit-Learn. This in-depth guide will walk you through the process of building machine learning models, from the ground up, using Scikit-Learn, one of the most widely used Python libraries for machine learning. Whether you're a beginner looking to dive into machine learning or an experienced data scientist seeking to master advanced techniques, this book will equip you with the tools and knowledge to build efficient and scalable models for real-world applications. Scikit-Learn provides simple and efficient tools for data analysis and machine learning. With its extensive functionality, this book will teach you how to implement various machine learning algorithms, such as classification, regression, clustering, and dimensionality reduction. You'll also explore key concepts like feature engineering, model evaluation, hyperparameter tuning, and how to apply these methods to solve real-world problems. Inside, you'll learn: The fundamentals of machine learning and the Scikit-Learn library How to preprocess data, including feature scaling, encoding categorical variables, and handling missing values The principles behind supervised learning algorithms like linear regression, decision trees, and support vector machines (SVMs) Techniques for unsupervised learning, including k-means clustering and principal component analysis (PCA) How to evaluate machine learning models using cross-validation, metrics like accuracy, precision, recall, and confusion matrices Advanced topics such as ensemble learning, random forests, and boosting methods Hyperparameter tuning techniques like GridSearchCV and RandomizedSearchCV for improving model performance How to deploy machine learning models and integrate them into production systems By the end of this book, you'll have the expertise to build and deploy machine learning models, from simple to complex, using Python and Scikit-Learn. Whether you're working on business analytics, predictive modeling, or artificial intelligence projects, Mastering Machine Learning with Python and Scikit-Learn will give you the skills to tackle a wide range of machine learning problems. Key Features: Master machine learning algorithms and techniques using Python and Scikit-Learn Step-by-step guidance for building, evaluating, and tuning machine learning models Practical examples and real-world case studies to apply machine learning to solve problems Advanced topics such as ensemble methods, hyperparameter tuning, and model deployment Best practices for preprocessing data, feature selection, and evaluating model performance Start mastering machine learning today with Mastering Machine Learning with Python and Scikit-Learn and take your data science and machine learning skills to the next level.