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Free Download Machine Learning Mastery: From Data To Decisions
English | December 22, 2025 | ASIN: B0GBYTJ3VZ | 122 pages | Epub | 1.20 MB
AI Insights Series Volume 2: Machine Learning Mastery - From Data to Decisions By James Head Book Description Building directly on the foundational knowledge from Volume 1, Machine Learning Mastery - From Data to Decisions takes you from curious beginner to confident practitioner. This hands-on volume demystifies the complete machine learning workflow, guiding you step-by-step through the process of turning raw data into accurate, actionable predictions and insights. Whether you're a business professional seeking to leverage data-driven decisions, a student preparing for a career in tech, or a developer ready to build your first real models, this book equips you with practical skills and deep understanding-no advanced mathematics degree required. What You'll Learn The Full Machine Learning Pipeline : Explore every stage from data collection and cleaning to model training, evaluation, and deployment. Learn why each step matters and how mistakes in one stage can cascade through the entire process. Data Preparation Mastery : Discover proven techniques for handling missing values, outliers, feature engineering, scaling, and encoding categorical variables-the often-overlooked steps that separate mediocre models from outstanding ones. Core Algorithms in Depth : Gain intuitive understanding (backed by clear visuals and real-world examples) of essential algorithms including linear regression, logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors, and clustering methods like k-means. Model Evaluation and Validation : Master metrics such as accuracy, precision, recall, F1-score, ROC-AUC, and confusion matrices. Learn cross-validation, train-test splits, and how to detect and prevent overfitting and underfitting. Practical Projects : Build and deploy complete models with guided, end-to-end projects including: Predicting house prices with regression Customer churn classification Credit risk assessment Market segmentation using clustering All projects include downloadable datasets and complete Python code. Tools and Best Practices : Work fluently with industry-standard libraries-Pandas for data manipulation, Scikit-learn for modeling, MatDescriptionlib and Seaborn for visualization-while learning workflow tips used by professional data scientists. Real-World Case Studies : See how companies like Netflix, Amazon, and healthcare providers apply these techniques to recommendation systems, fraud detection, personalized medicine, and inventory optimization. Written in the same accessible style as Volume 1, this book continues to use everyday analogies, avoids unnecessary jargon, and includes diagrams, code snippets, quizzes, and companion resources. By the end, you'll not only understand how machine learning works-you'll be able to apply it to solve real problems in your own domain. Perfect for readers who have completed Volume 1 or have basic familiarity with AI concepts and introductory Python. Ready to turn data into decisions? Volume 2 gives you the mastery you need to make it happen.

Free Download Machine Learning Engineering with Python: Build, Deploy, and Scale Real-World ML Systems with MLOps, Cloud Pipelines, and Production-Ready AI Solutions
English | November 17, 2025 | ASIN: B0G2CZ25BQ | 328 pages | Epub | 1.58 MB
Machine Learning Engineering with Python: Build, Deploy, and Scale Real-World ML Systems with MLOps, Cloud Pipelines, and Production-Ready AI Solutions This book gives you a practical roadmap for turning machine learning ideas into reliable, scalable, and production-ready systems. It guides you through the entire ML engineering lifecycle from data pipelines and model development to deployment, monitoring, scaling, and optimization using modern Python tools and proven MLOps practices. You explore how real-world AI systems work behind the scenes and learn how to build your own using cloud platforms, automation pipelines, and best-in-class engineering techniques. Designed for clarity and real-world relevance, this book shows you how to bridge the gap between experimentation and production. You move beyond notebooks and learn how to create ML solutions that run efficiently, scale seamlessly, and deliver consistent value. Summary You discover how to use Python, cloud services, CI/CD workflows, feature stores, orchestration frameworks, and containerized deployments to build robust machine learning systems. The book highlights the patterns used by experienced ML engineers, explains the pitfalls that often break production models, and provides the tools you need to design secure, efficient, and maintainable ML pipelines. Whether you're deploying models to the cloud, serving predictions in real time, or optimizing inference at scale, you gain the confidence to engineer solutions that meet real business needs. Key Features of This Book Covers the full ML engineering lifecycle from dataset design to scalable deployment Shows how to build end-to-end pipelines with MLOps tools and cloud platforms Explains real-world techniques for monitoring, observability, and continuous retraining Includes guidance on securing ML APIs, managing model lineage, and ensuring compliance Offers practical insights from real production environments Helps you understand both batch and streaming systems at scale Presents complex concepts in a simple, conversational, and SEO-optimized style This book is ideal for ML engineers, data scientists, software engineers, DevOps professionals, and students who want to master production-grade machine learning. If you're moving from experimentation to real deployments or aiming to design scalable, reliable AI systems this book gives you the structure and clarity you need. Beginners with Python experience and professionals seeking to upgrade their MLOps skills will also benefit greatly. If you're ready to build machine learning systems that perform reliably in the real world, scale effortlessly, and deliver measurable impact, this book is your complete guide. Take the next step in your ML engineering journey start reading today and learn how to transform models into production-ready AI solutions. Read more

Free Download Machine Learning: A Comprehensive Beginner's Guide by Akshay B R, Sini Raj Pulari, T S Murugesh
English | July 15, 2024 | ISBN: 1032676655 | 248 pages | EPUB | 51 Mb
Machine learning is a dynamic and rapidly expanding field focused on creating algorithms that empower computers to recognize patterns, make predictions and continually enhance performance. It enables computers to learn from data and experiences, making decisions without explicit programming. For learners, mastering the fundamentals of machine learning opens doors to a world of possibilities to build robust and accurate models. In the ever-evolving landscape of machine learning, datasets play a pivotal role in shaping its future. The field has been revolutionized with the introduction of oneAPI, which provides a unified programming model across different architectures, including CPUs, GPUs, FPGAs and accelerators, fostering an efficient and portable programming environment. Embracing this unified model empowers practitioners to build efficient and scalable machine learning solutions, marking a significant stride in cross-architecture development. Dive into this fascinating field to master machine learning concepts with the step-by-step approach outlined in this book and contribute to its exciting future.

Free Download Machine Learning & Data Science with Python for Beginners: Your Step-by-Step Guide to Starting a Career in ML and Data Analytics
English | December 10, 2025 | ASIN: B0G669GMVT | 56 pages | Epub | 250.96 KB
Are you ready to launch your career in one of today's most exciting and in-demand fields? This beginner-friendly guide is your complete roadmap to mastering machine learning and data science using Python - no prior experience required. Whether you're a student, a professional looking to reskill, or a curious self-learner, Machine Learning & Data Science with Python for Beginners takes you step-by-step through the core skills and practical tools you need to succeed in the world of AI and data-driven decision-making. What You'll Learn: The Basics of Python Programming Essential Data Science Techniques Fundamentals of Machine Learning Hands-On Practice Clear, Structured Learning Path If you're aiming to become a data analyst, machine learning engineer, or simply want to understand the technologies shaping the future, this book is the perfect place to start. Begin your journey today-and take the first step toward a career in machine learning and data science.

Free Download MY MENTORING DIARY: A Resource for the Library and Information Professions By Ann Ritchie, Paul Genoni
2007 | 88 Pages | ISBN: 159095811X | PDF | 1 MB
MY MENTORING DIARY A Resource for the Library and Information Professions A Practical Guide With Reflective Learning Journal To Help You Get the Most Out of Formal Mentoring My Mentoring Diary is designed as an introductory manual for all those engaged in a formal mentoring program. It provides general information about mentoring; practical tips and strategies for setting up a mentoring program; useful tips about how to get the most out of the mentoring experience; a guide for what to look for in a mentor; guidance on how to set individual objectives and a plan of action; and a Learning Journal section with lined and unlined pages for participants to record their reflections and thoughts about their experiences. This guide is especially helpful for mentors/mentorees who are not sure if they have the skills or are prepared to take on the responsibility of participating in a program. For those intending to set up a mentoring program, it provides the critical success factors to consider. The book is based on the extensive experience and insights of two librarians who specialize in mentoring programs. In 1995, Ann Ritchie and Paul Genoni established the Group Mentoring Program for graduate librarians as an initiative of the Western Australian branch of the Australian Library and Information Association. In addition to practical experience in individual and group mentoring, the authors have researched and evaluated mentoring programs, published and presented internationally on the topic, and have developed a workshop (How to Set Up a Facilitated Group Mentoring Program). They have received awards for mentoring services to the library profession and to university graduates. For other books about librarianship, please see the back of this book for a complete listing, or visit www.totalrecallpress.com for more information. Paul Genoni is a Senior Lecturer in the Faculty of Media, Society and Culture at Curtin University of Technology in Perth, Australia. He has published widely in a number of professional areas including collection management, reference, scholarly communication, mentoring and graduate destinations. Ann Ritchie is the Director of Library Services with the Department of Health and Community Services in Darwin, Australia, and previously worked as a reference librarian at Charles Darwin University. She has also served as database consultant for EBSCO Information Services. TABLE OF CONTENTS Using This Diary My Mentoring Contacts Section 1: Introduction to Mentoring What Is Mentoring? Why Is Mentoring Important? The Seven Stages of Mentoring NICE Analysis for Mentorees Setting Personal Objectives Making an Action Plan Making a Contract Section 2: Learning Journal Introduction What Is Reflective Practice? What Is a Learning Journal? Learning Journal Section 3: More about Mentoring Frequently Asked Questions (FAQs) Mentoring and Change Further Reading Organizations Notes

Free Download MT4/MT5 & Trading View High Probability Forex Trading Method (Forex, Forex Trading System, Forex Trading Strategy, Oil, Precious metals, Commodities, Stocks, Currency Trading, Bitcoin Book 2)
English | August 6, 2016 | ASIN: B01JURR1LE | 68 pages | EPUB (True) | 2.68 MB
Why Jim Brown's Books Are Amazon Best Sellers Jim Brown's books are renowned for delivering actionable insights that traders can immediately apply to their currency trading strategies. Here's why this book is essential for serious traders: Custom-Built Indicators: Access Jim's exclusive indicators for the MT4/MT5 MetaTrader platforms and TradingView. These tools are designed to help you identify high-probability trading opportunities, giving you a competitive edge in the Forex market. Active Trading Communities : Join Jim's Facebook and Telegram Groups, where around 10,000 Forex traders share insights, discuss strategies, and interact with Jim daily. This vibrant community offers invaluable support for anyone involved in currency trading. Live Trades and Analysis: Follow Jim's live trade calls, results, and weekly analysis videos on YouTube. See his trading strategies in action and refine your approach to the global economy and exchange rates. Direct Access to Jim: Have questions? Jim provides direct support to his readers, ensuring you get the guidance needed to implement his high-probability trading methods successfully. About the Book MT4/MT5 & TradingView High Probability Forex Trading Method introduces a robust trading approach refined through extensive demo and live trading. Designed for MT4/MT5 and TradingView, this method is ideal for leveraging these platforms in the Forex market. Though focused on currency pairs, Jim's method is versatile enough for other financial markets such as: Oil Precious metals Commodities Stock indices Individual stocks Cryptocurrencies You can use Jim's custom indicators on a MT4/MT5 or TradingView demo account for analysis, even if you prefer another trading platform. This approach ensures a clear, strategic method for risk management, helping you maximize profits and minimise losses. Why This Book Is Essential This book is perfect for traders serious about improving their success in the Forex market. Built on principles of patience, discipline, and strategic analysis, Jim's method remains as relevant today as when first introduced. Explore Jim Brown's Complete Collection on Amazon Expand your knowledge with Jim's other best-selling books: Forex Trading: The Basics Explained in Simple Terms - Ideal for beginners entering currency trading. MT4/MT5 and TradingView High Probability Forex Trading Method - Maximize your success with high-probability trades-this book! Trading Forex with Divergence on MT4/MT5 & TradingView - Advance your trading with divergence techniques. Forex Trading Journal: Patience, Courage, Discipline - Master the psychological aspects of trading. Profitable Forex Trading Using High and Low Risk Strategies - Balance risk and reward with tailored strategies. Featured in Leading Trading Podcasts Jim's expertise has been highlighted on: Desire to Trade Podcast with Etienne Crete Trading Nuts Podcast with Cam Hawkins Join thousands of successful traders and take control of your Forex trading journey with Jim Brown's MT4/MT5 & TradingView High Probability Forex Trading Method. Whether navigating currency pairs, managing exchange rates, or thriving in the global economy, this book provides the tools and strategies to help you succeed.

Free Download MKSAP 19: medical knowledge self-assessment program. Rheumatology By American College of Physicians
2021 | 194 Pages | ISBN: 193824575X | PDF | 147 MB
ExaminationsExamination QuestionsOutlineExaminations, questions, etcDavoren Chick, editor-in-chief."Approved for AMA PRA Category 1 credits available until August 31, 2024.MKSAP 19 contains 2 parts, Part A and Part B - each part consists of a number of individual volumes.12 volumes : illustrations (some color) ; 28 cm + 2 sheetsPart A:[v.1] Gastroenterology and hepatology --[v.2] General internal medicine 1 --[v.3] Infectious disease --[v.4] Nephrology --[v.5] Neurology --[v.6] Oncology --Part B: [v.1] Cardiovascular medicine --[v.2] Endocrinology and metabolism --[v.3] General internal medicine 2 --[v.4] Hematology --[v.5] Pulmonary and critical care medicine --[v. 6] Rheumatology.

Free Ebooks Download

Why Choose DL4ALL.org?

Machine Learning and Deep Learning Using Python and TensorFlow

Machine Learning Mastery From Data To Decisions

Machine Learning Fundamentals Concepts, Models, and Applications

Machine Learning For Dummies, 3rd Edition

Machine Learning Engineering with Python Build, Deploy, and Scale Real-World ML Systems with MLOps, Cloud Pipelines

Machine Learning A Comprehensive Beginner's Guide

Machine Learning & Data Science with Python for Beginners Your Step-by-Step Guide to Starting a Career in ML

MY MENTORING DIARY A Resource for the Library and Information Professions

MT4MT5 & Trading View High Probability Forex Trading Method

MKSAP 19 medical knowledge self-assessment program. Rheumatology