Learn Machine Learning in 24 Hours [ebook]
Master the Basics of Machine Learning in Just 24 Hours and Unlock the Power of AI and Data Science!
Language - English
Updated on Feb, 2025
About the Book
Book description
Unlock the Power of AI with Learn Machine Learning in 24 Hours: The Ultimate Beginner’s Guide
This is your comprehensive path to mastering machine learning in just one day! Designed for both beginners and coders, this machine learning for dummies guide simplifies complex concepts and empowers you to build intelligent systems with ease. Whether you're a data enthusiast, programmer, or professional looking to break into AI and machine learning for coders, this hands-on book will guide you from foundational knowledge to advanced applications.
Why Learn Machine Learning?
Machine learning is at the forefront of technological innovation, powering everything from personalized recommendations to algorithmic trading and autonomous systems. With its increasing demand across industries, aspiring tech professionals and innovators must gain a strong grasp of why machines learn and how to create intelligent models. This book provides an accelerated learning path, offering a practical approach to building machine learning solutions.
What’s Inside?
"Learn Machine Learning in 24 Hours" is divided into carefully structured lessons that transform you from a novice to an AI practitioner:
- Hour 1-2: Overview of machine learning, applications, history, and Python setup.
- Hour 3-5: Data types, collection, preprocessing, and intro to supervised learning.
- Hour 6-8: Regression, Decision Trees, Random Forests, and SVM basics.
- Hour 9-11: KNN, Naive Bayes, and unsupervised learning concepts.
- Hour 12-14: K-Means, Hierarchical Clustering, and PCA.
- Hour 15-17: Neural networks basics, TensorFlow/Keras, CNNs, and RNNs.
- Hour 18-20: Model evaluation, tuning, and deployment.
- Hour 21-23: Reinforcement learning and real-world project pitfalls.
- Hour 24: Final project: building and deploying an ML solution.
Who Should Read This Book?
This guide is perfect for:
- Absolute beginners looking for a simple yet effective way to learn machine learning for absolute beginners with Python.
- Coders and developers seeking to add machine learning for coders to their programming expertise.
- Professionals in finance, healthcare, and tech aiming to master machine learning for algorithmic trading and decision-making tools.
What You’ll Learn:
- Effortless Python setup for machine learning.
- Core machine learning concepts like supervised and unsupervised learning.
- Building, training, and optimizing machine learning models.
- Data handling with NumPy, pandas, and data visualization with Matplotlib and Seaborn.
- The power of neural networks for image and text classification.
- Real-world applications like algorithmic trading, fraud detection, and predictive analytics.
- Integration of machine learning models into API services and web apps using Flask.
- Best practices for debugging, tuning, and deploying models on the cloud.
Why This Book?
This machine learning for beginners book takes a hands-on approach, simplifies explanations, and provides plenty of practical coding examples. It will help you gain confidence and competence. You’ll also learn how to avoid common pitfalls and adopt best practices for creating scalable, efficient machine learning solutions.
Whether you're aiming to enhance your programming portfolio, break into AI, or create impactful solutions for business and research, this guide equips you with everything you need to succeed in your machine-learning journey.
Get started today and discover the limitless possibilities of machine learning in just 24 hours!
Goals
- Understand Machine Learning Basics: Learn the foundational concepts of machine learning, including its applications, history, and types.
- Master Data Handling: Gain proficiency in data collection, preprocessing, and cleaning using Python libraries like NumPy and Pandas.
- Learn Supervised Learning: Build and train models using techniques like Linear Regression, Decision Trees, Random Forests, and Support Vector Machines (SVMs).
- Explore Unsupervised Learning: Understand clustering techniques like K-Means and Hierarchical Clustering and dimensionality reduction methods like PCA.
- Dive into Neural Networks: Get introduced to neural networks, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) using TensorFlow and Keras.
- Perform Model Evaluation: Learn how to evaluate, debug, and optimize models for improved performance.
- Build and Deploy ML Models: Develop end-to-end machine learning solutions and deploy them as APIs using Flask.
- Understand Reinforcement Learning: Grasp the basics of reinforcement learning and its real-world applications.
- Work on Real-World Projects: Apply your knowledge to hands-on projects like algorithmic trading, fraud detection, and predictive analytics.
- Develop Career-Ready Skills: Gain practical insights and best practices for debugging, model tuning, and deployment on cloud platforms.
![Learn Machine Learning in 24 Hours [ebook] Learn Machine Learning in 24 Hours [ebook]](https://d3mxt5v3yxgcsr.cloudfront.net/courses/21150/course_21150_image.jpg)
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Author Details

<a href="https://market.tutorialspoint.com/author/aniket_jain">Aniket Jain</a>
Full Stack DeveloperOur students work
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