Mastering Ai And Machine Learning With Python
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Mastering Ai And Machine Learning With Python
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Author : Anshuman Mishra
language : en
Publisher: Independently Published
Release Date : 2025-05-12
Mastering Ai And Machine Learning With Python written by Anshuman Mishra and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-12 with Computers categories.
This ambitious two-volume work, "Mastering AI and Machine Learning with Python: From Fundamentals to Advanced Deep Learning," aims to be a definitive guide for anyone seeking to understand, implement, and master the intricate world of Artificial Intelligence (AI) and Machine Learning (ML) using the versatile Python programming language. Spanning a projected 10,000 words across both volumes (with Volume 1 detailed below), this book meticulously progresses from foundational concepts to cutting-edge deep learning techniques, providing readers with a robust theoretical understanding coupled with practical implementation skills. Volume 1: Foundations and Core Machine Learning Techniques Volume 1 lays the essential groundwork for embarking on the journey of AI and ML. It is structured to take individuals with varying levels of prior knowledge - from complete beginners to those with some programming experience - and equip them with the core competencies required to understand and apply fundamental machine learning algorithms. Chapter 1: Introduction to AI and Machine Learning This introductory chapter serves as a compass, orienting the reader within the broad landscape of AI and its subfields. It begins by clearly delineating the concepts of Artificial Intelligence, Machine Learning, and Deep Learning, highlighting their relationships and distinctions. Understanding AI, Machine Learning, and Deep Learning: This section meticulously unpacks these often-interchangeable terms. It defines AI as the overarching field focused on creating intelligent agents capable of performing tasks that typically require human intelligence. Machine Learning is then presented as a subset of AI, where systems learn from data without being explicitly programmed. Finally, Deep Learning is introduced as a subfield of ML that utilizes artificial neural networks with multiple layers (deep neural networks) to extract complex patterns from large datasets. The chapter will use analogies and real-world examples to solidify these definitions, ensuring a clear understanding of the hierarchy and unique characteristics of each field. Real-World Applications of AI: To underscore the practical relevance and transformative power of AI, this section delves into a diverse range of real-world applications. It will explore how AI is revolutionizing industries such as healthcare (diagnosis, drug discovery), finance (fraud detection, algorithmic trading), transportation (autonomous vehicles), entertainment (recommendation systems), manufacturing (predictive maintenance), and customer service (chatbots). Each application will be briefly described, highlighting the specific AI techniques employed and the tangible benefits realized. This section aims to inspire the reader and contextualize the learning journey ahead. The Role of Python in AI Development: This crucial segment emphasizes why Python has emerged as the lingua franca of AI and ML. It will discuss Python's key advantages, including its clear and concise syntax, extensive ecosystem of powerful libraries (such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch), large and active community support, and its versatility for various stages of the AI development lifecycle - from data preprocessing to model deployment. The chapter will briefly introduce some of these key libraries, setting the stage for their detailed exploration in subsequent chapters. Overview of TensorFlow and PyTorch: As two of the most prominent deep learning frameworks, TensorFlow and PyTorch are introduced in this section. The chapter will provide a high-level overview of their functionalities, key features, and their respective strengths and weaknesses. It will touch upon their roles in building and training neural networks, their support for hardware acceleration (GPUs), and their growing adoption in both research and industry.
Generative Deep Learning With Python
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Author : Cuantum Technologies LLC
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-12
Generative Deep Learning With Python written by Cuantum Technologies LLC 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 2024-06-12 with Computers categories.
Dive into the world of Generative Deep Learning with Python, mastering GANs, VAEs, & autoregressive models through projects & advanced topics. Gain practical skills & theoretical knowledge to create groundbreaking AI applications. Key Features Comprehensive coverage of deep learning and generative models. In-depth exploration of GANs, VAEs, & autoregressive models & advanced topics in generative AI. Practical coding exercises & interactive assignments to build your own generative models. Book DescriptionGenerative Deep Learning with Python opens the door to the fascinating world of AI where machines create. This course begins with an introduction to deep learning, establishing the essential concepts and techniques. You will then delve into generative models, exploring their theoretical foundations and practical applications. As you progress, you will gain a deep understanding of Generative Adversarial Networks (GANs), learning how they function and how to implement them for tasks like face generation. The course's hands-on projects, such as creating GANs for face generation and using Variational Autoencoders (VAEs) for handwritten digit generation, provide practical experience that reinforces your learning. You'll also explore autoregressive models for text generation, allowing you to see the versatility of generative models across different types of data. Advanced topics will prepare you for cutting-edge developments in the field. Throughout your journey, you will gain insights into the future landscape of generative deep learning, equipping you with the skills to innovate and lead in this rapidly evolving field. By the end of the course, you will have a solid foundation in generative deep learning and be ready to apply these techniques to real-world challenges, driving advancements in AI and machine learning.What you will learn Develop a detailed understanding of deep learning fundamentals Implement and train Generative Adversarial Networks (GANs) Create & utilize Variational Autoencoders for data generation Apply autoregressive models for text generation Explore advanced topics & stay ahead in the field of generative AI Analyze and optimize the performance of generative models Who this book is for This course is designed for technical professionals, data scientists, and AI enthusiasts who have a foundational understanding of deep learning and Python programming. It is ideal for those looking to deepen their expertise in generative models and apply these techniques to innovative projects. Prior experience with neural networks and machine learning concepts is recommended to maximize the learning experience. Additionally, research professionals and advanced practitioners in AI seeking to explore generative deep learning applications will find this course highly beneficial.
Mastering Ai With Python
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Author : Elian Greystone
language : en
Publisher: Independently Published
Release Date : 2025-07-11
Mastering Ai With Python written by Elian Greystone and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-11 with Computers categories.
Harness the Power of AI - with the Language of the Future. Mastering AI with Python is a hands-on, step-by-step guide to learning the core principles of artificial intelligence and applying them using Python, the most popular language in AI today. Whether you're a beginner or a developer transitioning into AI, this book equips you with the tools, libraries, and real-world techniques to build intelligent systems that learn, adapt, and solve real problems. You'll cover everything from machine learning fundamentals to building AI-powered applications with tools like Scikit-learn, TensorFlow, Keras, OpenCV, and Natural Language Toolkit (NLTK). With projects covering computer vision, NLP, recommendation systems, and more, you'll gain the confidence to deploy your own AI solutions in production.
Mastering Reinforcement Learning With Python
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Author : Enes Bilgin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-12-18
Mastering Reinforcement Learning With Python written by Enes Bilgin 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 2020-12-18 with Computers categories.
Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry problems with the help of expert tips and best practices Key FeaturesUnderstand how large-scale state-of-the-art RL algorithms and approaches workApply RL to solve complex problems in marketing, robotics, supply chain, finance, cybersecurity, and moreExplore tips and best practices from experts that will enable you to overcome real-world RL challengesBook Description Reinforcement learning (RL) is a field of artificial intelligence (AI) used for creating self-learning autonomous agents. Building on a strong theoretical foundation, this book takes a practical approach and uses examples inspired by real-world industry problems to teach you about state-of-the-art RL. Starting with bandit problems, Markov decision processes, and dynamic programming, the book provides an in-depth review of the classical RL techniques, such as Monte Carlo methods and temporal-difference learning. After that, you will learn about deep Q-learning, policy gradient algorithms, actor-critic methods, model-based methods, and multi-agent reinforcement learning. Then, you'll be introduced to some of the key approaches behind the most successful RL implementations, such as domain randomization and curiosity-driven learning. As you advance, you’ll explore many novel algorithms with advanced implementations using modern Python libraries such as TensorFlow and Ray’s RLlib package. You’ll also find out how to implement RL in areas such as robotics, supply chain management, marketing, finance, smart cities, and cybersecurity while assessing the trade-offs between different approaches and avoiding common pitfalls. By the end of this book, you’ll have mastered how to train and deploy your own RL agents for solving RL problems. What you will learnModel and solve complex sequential decision-making problems using RLDevelop a solid understanding of how state-of-the-art RL methods workUse Python and TensorFlow to code RL algorithms from scratchParallelize and scale up your RL implementations using Ray's RLlib packageGet in-depth knowledge of a wide variety of RL topicsUnderstand the trade-offs between different RL approachesDiscover and address the challenges of implementing RL in the real worldWho this book is for This book is for expert machine learning practitioners and researchers looking to focus on hands-on reinforcement learning with Python by implementing advanced deep reinforcement learning concepts in real-world projects. Reinforcement learning experts who want to advance their knowledge to tackle large-scale and complex sequential decision-making problems will also find this book useful. Working knowledge of Python programming and deep learning along with prior experience in reinforcement learning is required.
Mastering Ai And Machine Learning With Python
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Author : Anshuman Mishra
language : en
Publisher: Independently Published
Release Date : 2025-05-12
Mastering Ai And Machine Learning With Python written by Anshuman Mishra and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-12 with Computers categories.
Chapter 9: Convolutional Neural Networks (CNNs) This chapter likely begins by revisiting the fundamental concepts of convolutional operations. It would meticulously explain how convolution works, including the roles of filters (kernels), strides, padding, and activation functions in extracting meaningful features from image data. The concept of feature maps, which represent the output of applying filters at different layers, would be thoroughly discussed, emphasizing how these maps capture hierarchical representations of visual information. The chapter would then transition into exploring various influential CNN architectures. LeNet: This pioneering CNN architecture, designed for handwritten digit recognition, would be presented as a foundational example, illustrating the basic building blocks of a CNN. Its layers, including convolutional layers, pooling layers (like average pooling), and fully connected layers, would be explained in detail. The historical significance of LeNet in the development of modern CNNs would also likely be highlighted. AlexNet: This groundbreaking architecture, which achieved remarkable success in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), would be analyzed for its key innovations. These include the use of ReLU activation functions, dropout for regularization, and the utilization of multiple GPUs for training. The impact of AlexNet on the field of computer vision and the resurgence of deep learning would be emphasized. VGG (Visual Geometry Group): The chapter would delve into the VGG networks, known for their deep and uniform architectures consisting of small convolutional filters stacked together. The concepts of VGG16 and VGG19, along with their consistent use of 3×3 convolutional kernels, would be explained. The advantages and limitations of VGG networks, such as their depth and large number of parameters, would likely be discussed. ResNet (Residual Network): This architecture, which addressed the vanishing gradient problem in very deep networks through the introduction of residual connections (skip connections), would be thoroughly examined. The concept of identity mappings and how they facilitate the training of extremely deep networks would be explained. Different ResNet variants (e.g., ResNet-50, ResNet-101) and their performance benefits would likely be covered. Finally, the chapter would explore the applications of CNNs in: Image Classification: This fundamental task of assigning a label to an entire image based on its content would be discussed. Different loss functions (e.g., cross-entropy) and evaluation metrics (e.g., accuracy, F1-score) used in image classification would be explained. Object Detection: This more complex task of identifying and localizing multiple objects within an image using bounding boxes would be introduced. Early object detection architectures and the fundamental challenges involved would likely be discussed, setting the stage for more advanced techniques covered in later chapters. Chapter 10: Recurrent Neural Networks (RNNs) and LSTMs This chapter would shift focus to sequential data and how Recurrent Neural Networks (RNNs) are designed to process it. The fundamental concept of how RNNs maintain an internal state (memory) to handle sequences would be explained, along with the challenges associated with training vanilla RNNs, such as the vanishing and exploding gradient problems.
Mastering Ai And Machine Learning In The Real World With Hands On Projects
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Author : Morgan Steele
language : en
Publisher: Independently Published
Release Date : 2025-06-15
Mastering Ai And Machine Learning In The Real World With Hands On Projects written by Morgan Steele and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-15 with categories.
Artificial Intelligence & Machine Learning By Morgan Steele Master Modern AI with Real-World Applications, Hands-On Projects, and Clear Explanations Unlock the power of AI and machine learning with this practical guide designed for developers, analysts, and tech professionals at every level. Whether you're building intelligent systems, exploring generative AI, or preparing for a career in data science, this book provides the tools and knowledge to get you there. Inside, you'll learn: Core concepts of AI and how machines learn Supervised, unsupervised, and reinforcement learning explained with examples Essential tools like Python, Scikit-learn, TensorFlow, and Hugging Face How to prepare and clean real-world data for training Building, evaluating, and comparing ML models Deploying models with Flask and APIs Prompt engineering and LLM integration using OpenAI and LangChain Each chapter is packed with visual guides, hands-on coding projects, and actionable insights. Whether you're a beginner or expanding your skills, this is your complete starting point for mastering AI. Join thousands of learners unlocking the future of technology-one model at a time.
Mastering Machine Learning On Aws
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Author : Dr. Saket S.R. Mengle
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-20
Mastering Machine Learning On Aws written by Dr. Saket S.R. Mengle 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 2019-05-20 with Computers categories.
Gain expertise in ML techniques with AWS to create interactive apps using SageMaker, Apache Spark, and TensorFlow. Key FeaturesBuild machine learning apps on Amazon Web Services (AWS) using SageMaker, Apache Spark and TensorFlowLearn model optimization, and understand how to scale your models using simple and secure APIsDevelop, train, tune and deploy neural network models to accelerate model performance in the cloudBook Description AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud. As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every practical application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics, and predictive modeling, through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS. What you will learnManage AI workflows by using AWS cloud to deploy services that feed smart data productsUse SageMaker services to create recommendation modelsScale model training and deployment using Apache Spark on EMRUnderstand how to cluster big data through EMR and seamlessly integrate it with SageMakerBuild deep learning models on AWS using TensorFlow and deploy them as servicesEnhance your apps by combining Apache Spark and Amazon SageMakerWho this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and AWS users who want to build advanced models and smart applications on the cloud using AWS and its integration services. Some understanding of machine learning concepts, Python programming and AWS will be beneficial.
Mastering Machine Learning With Core Ml And Python
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Author : Vardhan Agrawal
language : en
Publisher: AppCoda
Release Date : 2020-08-13
Mastering Machine Learning With Core Ml And Python written by Vardhan Agrawal and has been published by AppCoda this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-13 with Computers categories.
Machine learning, now more than ever, plays a pivotal role in almost everything we do in our digital lives. Whether it’s interacting with a virtual assistant like Siri or typing out a message to a friend, machine learning is the technology facilitating those actions. It’s clear that machine learning is here to stay, and as such, it’s a vital skill to have in the upcoming decades. This book covers Core ML in-depth. You will learn how to create and deploy your own machine learning model. On top of that, you will learn about Turi Create, Create ML, Keras, Firebase, and Jupyter Notebooks, just to name a few. These are a few examples of professional tools which are staples for many machine learning experts. By going through this book, you’ll also become proficient with Python, the language that’s most frequently used for machine learning. Plus, you would have created a handful of ready-to-use apps such as barcode scanners, image classifiers, and language translators. Most importantly, you will master the ins-and-outs of Core ML.
Machine Learning With Python
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Author : Russel R Russo
language : en
Publisher:
Release Date : 2021-02-04
Machine Learning With Python written by Russel R Russo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-04 with categories.
Are you fascinated by Machine Learning but it seems too complicated?Do you have some coding skills but you want to go deeper in Python and Machine Learning? If this is you, please keep reading: you are in the right place, looking at the right book. Since you are reading this you are probably aware of how important Artificial Intelligence is in these days. In your everyday life Artificial Intelligence is all around you. Every time you buy a product on Amazon, follow a new profile on Instagram, listen to a song on Spotify or reserve a room on Booking, they are learning something out of your behavior. And these are just the most visible aspects of how Machine Learning is having an impact on our lives. Everyone knows (well, almost everyone) how important Machine Learning is for the growth and success of the biggest tech companies, and many people know about the Machine Learning impact in science, medicine and statistics. Also, it is quite commonly known that Artificial Intelligence, Machine Learning, and the mastering of their most important language, Python, can offer a lot of possibilities in work and business. And you yourself are probably thinking "I surely can see that opportunity, but how can I seize it?" Well, if you kept reading so far you are on the right track to answer your question. In Machine Learning with Python you will find: Why python is the best language for Machine Learning How to bring your ideas into a computer The smartest way to approach Machine Learning How to deal with variables and data Tips and tricks for a smooth and painless journey into artificial intelligence The most common myths about Machine Learning debunked So, whether you decided to start now or to go deeper into Artificial Intelligence, Machine Learning and Python Programming, you will only have two unanswered questions right now: "what is the best way to do it? And when is the best time to start?" An easy, clear and complete guide as Machine Learning with Python is the answer to your first question, and about the second one, well, that's an easy one: the best time is NOW! Buy Machine Learning with Python now and start mastering the secrets of Artificial Intelligence.
A Complete Tutorial
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Author : Austin Wren
language : en
Publisher: Independently Published
Release Date : 2025-03-03
A Complete Tutorial written by Austin Wren and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-03 with Computers categories.
Master the Art of Machine Learning with Python: From Beginner to Expert Unlock the potential of machine learning with "A Complete Tutorial: Mastering Machine Learning with Python," your comprehensive guide to the exciting world of artificial intelligence. Authored by Austin Wren, this book is designed for learners of all levels, providing an in-depth exploration of machine learning from basic concepts to advanced techniques. What You Will Learn: Python Basics: Refresh your Python skills with a complete Python crash course necessary for machine learning. Data Handling: Master the art of processing and preparing data, ensuring your models have the best foundation for success. Core Machine Learning Algorithms: Dive into a variety of algorithms, including regression, decision trees, and neural networks, and understand when and how to use them effectively. Advanced Techniques: Advance your skills with techniques like model optimization, hyperparameter tuning, and ensemble learning to improve your model's accuracy and efficiency. Practical Projects: Apply your knowledge with real-world projects that cover predicting sales, image classification, and sentiment analysis. Why This Book? Hands-On Approach: Each chapter includes practical examples and exercises to reinforce learning, making complex concepts accessible. Latest Tools and Technologies: Learn with the latest Python libraries and tools, ensuring you are up to speed with industry standards. Expert Insights: Gain insights from Austin Wren's extensive experience in machine learning, providing you with tips and tricks that go beyond the basics. Perfect for: Beginners looking to make a strong start in machine learning. Intermediate learners wanting to deepen their understanding of specific machine learning aspects. Professionals seeking to enhance their skills in practical machine learning applications. About the Author: Austin Wren is a renowned data scientist and educator in the field of machine learning, with over a decade of experience in turning data into actionable insights. Get ready to transform your understanding of machine learning and turn knowledge into action. Dive into "A Complete Tutorial: Mastering Machine Learning with Python" and begin your journey to becoming a machine learning expert today! Available exclusively on Amazon.