Download or read book Ultimate Step by Step Guide to Deep Learning Using Python written by Daneyal Anis and published by . This book was released on 2020-07-19 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: *Start your Data Science career using Python today!*Are you ready to start your new exciting career? Ready to master artificial intelligence and deep learning concepts?Are you overwhelmed with complexity of the books on this subject?Then let this breezy and fun little book on Python, Machine Learning and Deep Learning models make you a Data Scientist in 7 days!This book continues from where the first book in the series, Ultimate Step by Step Guide to Machine Learning Using Python, left of. In the first book you were introduced to Python concepts such as: -Data Structures like Pandas -Foundational libraries like Numpy, Seaborn and Scikit-Learn-Regression analysis-Classification-Clustering-Association Learning-Dimension ReductionThis book builds on those concepts to expand on Machine Learning algorithms like: -Linear and Logistical regression-Decision tree-Support vector machines (SVM)After that, this book takes you on a journey into Deep Learning and Neural Networks with important concepts and libraries like: -Convolutional and Recurrent Neural Networks-TensorFlow-Keras-PyTorch-Keras-Apache MXNet-Microsoft Cognitive Toolkit (CNTK)The final part of the book covers all foundational concepts that are required for Amazon Web Services (AWS) Certified Machine Learning Specialization by explaining how to deploy your models at scale on Cloud technologies. While AWS is used in the book for illustrative purposes, Microsoft Azure and Google Cloud are also introduced as alternative cloud technologies. After reading this book you will be able to: -Code in Python with confidence-Build new machine learning and deep learning models from scratch-Know how to clean and prepare your data for analytics-Speak confidently about statistical analysis techniquesData Science was ranked the fast-growing field by LinkedIn and Data Scientist is one of the most highly sought after and lucrative careers in the world!If you are on the fence about making the leap to a new and lucrative career, this is the book for you!What sets this book apart from other books on the topic of Python and Machine learning: -Step by step code examples and explanation-Complex concepts explained visually-Real world applicability of the machine learning and deep learning models introducedWhat do I need to get started?You will have a step by step action plan in place once you finish this book and finally feel that you, can master data science and artificial intelligence and start a lucrative and rewarding career! Ready to dive in to the exciting world of Python and Deep Learning?Then scroll up to the top and hit that BUY BUTTON!

Download or read book Ultimate Step by Step Guide to Machine Learning Using Python written by Daneyal Anis and published by . This book was released on 2020-02-17 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: *Start your Data Science career using Python today!* Are you ready to start your new exciting career? Ready to crush your machine learning career goals? Are you overwhelmed with complexity of the books on this subject?Then let this breezy and fun little book on Python and machine learning models make you a data scientist in 7 days! First part of this book introduces Python basics including: 1) Data Structures like Pandas 2) Foundational libraries like Numpy, Seaborn and Scikit-Learn Second part of this book shows you how to build predictive machine learning models step by step using techniques such as: 1) Regression analysis 2) Decision tree analysis 3) Training and testing data models 4) And much more! After reading this book you will be able to: 1) Code in Python with confidence 2) Build new machine learning models from scratch 3) Know how to clean and prepare your data for analytics 4) Speak confidently about statistical analysis techniques Data Science was ranked the fast-growing field by LinkedIn and Data Scientist is one of the most highly sought after and lucrative careers in the world! If you are on the fence about making the leap to a new and lucrative career, this is the book for you! What sets this book apart from other books on the topic of Python and Machine learning: 1) Step by step code examples and explanation 2) Complex concepts explained visually 3) Real world applicability of the machine learning models introduced 4) Bonus free code samples that you can try yourself without any prior experience in Python! What do I need to get started? You will have a step by step action plan in place once you finish this book and finally feel that you, can master data science and machine learning and start lucrative and rewarding career! Ready to dive in to the exciting world of Python and Machine Learning? Then scroll up to the top and hit that BUY BUTTON!

Download or read book Mastering Deep Learning Fundamentals with Python written by Richard Wilson and published by Independently Published. This book was released on 2019-07-14 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★ Step into the fascinating world of data science.. You to participate in the revolution that brings artificial intelligence back to the heart of our society, thanks to data scientists. Data science consists in translating problems of any other nature into quantitative modeling problems, solved by processing algorithms. This book, designed for anyone wishing to learn Deep Learning. This book presents the main techniques: deep neural networks, able to model all kinds of data, convolution networks, able to classify images, segment them and discover the objects or people who are there, recurring networks, it contains sample code so that the reader can easily test and run the programs. On the program: Deep learning Neural Networks and Deep Learning Deep Learning Parameters and Hyper-parameters Deep Neural Networks Layers Deep Learning Activation Functions Convolutional Neural Network Python Data Structures Best practices in Python and Zen of Python Installing Python Python These are some of the topics covered in this book: fundamentals of deep learning fundamentals of probability fundamentals of statistics fundamentals of linear algebra introduction to machine learning and deep learning fundamentals of machine learning fundamentals of neural networks and deep learning deep learning parameters and hyper-parameters deep neural networks layers deep learning activation functions convolutional neural network Deep learning in practice (in jupyter notebooks) python data structures best practices in python and zen of python installing python The following are the objectives of this book: To help you understand deep learning in detail To help you know how to get started with deep learning in Python by setting up the coding environment. To help you transition from a deep learning Beginner to a Professional. To help you learn how to develop a complete and functional artificial neural network model in Python on your own. And more Get this book now to learn more about -- Deep learning in Python by setting up the coding environment.!

Download or read book Deep Learning With Python written by Ethan Williams and published by . This book was released on 2020-05-27 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction 1Deep Learning with Python - The ultimate beginners guide to Learn Deep Learning with Python Step by StepYou have made a perfect choice to consider learning Python and most importantly to develop your skills in the programming world. A good choice comes with good tidings since you have you are looking at a highly comprehensive beginners' guidebook that will provide you with all the necessary steps and tips to get started. Deep Learning with Python - The ultimate beginners guide to Learn Deep Learning with Python Step by Step is packed with basic beginners' concepts, detailed examples and extra reminder exercises.Newbies are totally welcome to dive in! You do not need any experience with programming whatsoever. Just have a notepad ready because taking short notes helps and get ready to play around with the samples and do a whole lot of coding!The program was developed in December 1989 by Guido van Rossum. Guido's passion and hobby was to write and learn new codes that were available during his time. It is documented that he developed the python programming language while interacting and learning the ABC programming language.This is one of the best languages that you can choose to begin learning and at the end have a successful career in it. In summary, since the programming language was open-sourced, we expect a lot of advancements and developments on the language that will make it simpler and easier to use over the coming years.Introduction 2Deep Learning with Python - Comprehensive Guide of Tips and Tricks using Deep Learning with Python TheoriesThis book is designed to help you use Python for deep learning, including how to build and run deep learning models using Keras. This book also includes deep learning techniques, sample code, and technical content.The mathematical foundations of deep learning are subtle: but the average user doesn't need to fully understand the mathematical details to pick up the keyboard and start programming. Practically speaking, deep learning is not complicated, but the results are very objective. Teach you how to use deep learning: this is the purpose of this book.Introduction 3Deep Learning with Python - Advanced and Effective Strategies of Using Deep Learning with Python TheoriesThis book discusses the intricacies of the internal workings of a deep learning model. It addresses the techniques and methods that can not only boost the productivity of your machine learning architectural skills, but also introduces new concepts. Implemented correctly, these can set your deep learning model a league apart from all other models. This book not only focuses on theoretical and conceptual realms of such knowledge, but also gives equal importance to putting this information to the test. We do this by including some common practical examples and demonstrations that you would normally build deep learning for, hence giving you the best of both worlds. The main features of this book include: -Refreshing the fundamentals of a deep learning model and neural networks and connecting them with the advanced knowledge laid out in this book, reinforcing the reader's prior knowledge and transforming it into an expert-level understanding.-Emphasizing those tasks that are commonly demanded from deep learning models and breathing new life into them by introducing new techniques, methods, and elements that enable the model to drastically improve the performance of deep learning models on such tasks.-No usage of mathematical notations in the examples detailed in this book so that the concepts can be readily assimilated and mastered by programmers that do not have a mathematical background, hence prioritizing clarity of concepts.-Keeping this requirement in mind, the examples use Numpy code throughout as it best represents what the code actually means and its purpose.If you want to learn advanced strategies for Python this is the book for you.

Download or read book Deep Learning with Python written by Mark Graph and published by . This book was released on 2019-10-15 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book doesn't have any superpowers or magic formula to help you master the art of neural networks and deep learning. We believe that such learning is all in your heart. You need to learn a concept by heart and then brainstorm its different possibilities. I don't claim that after reading this book you will become an expert in Python and Deep Learning Neural Networks. Instead, you will, for sure, have a basic understanding of deep learning and its implications and real-life applications. Most of the time, what confuses us is the application of a certain thing in our lives. Once we know that, we can relate the subject to that particular thing and learn. An interesting thing is that neural networks also learn the same way. This makes it easier to learn about them when we know the basics. Let's take a look at what this book has to offer: ● The basics of Python including data types, operators and numbers. ● Advanced programming in Python with Python expressions, types and much more. ● A comprehensive overview of deep learning and its link to the smart systems that we are now building. ● An overview of how artificial neural networks work in real life. ● An overview of PyTorch. ● An overview of TensorFlow. ● An overview of Keras. ● How to create a convolutional neural network. ● A comprehensive understanding of deep learning applications and its ethical implications, including in the present and future. This book offers you the basic knowledge about Python and Deep Learning Neural Networks that you will need to lay the foundation for future studies. This book will start you on the road to mastering the art of deep learning neural networks. When I say that I don't have the magic formula to make you learn, I mean it. My point is that you should learn Python coding and Python libraries to build neural networks by practicing hard. The more you practice, the better it is for your skills. It is only after thorough and in depth practice that you will be able to create your own programs. Unlike other books, I don't claim that this book will make you a master of deep learning after a single read. That's not realistic, in fact, it's even a bit absurd. What I claim is that you will definitely learn about the basics. The rest is practice. The more you practice the better you code.

Download or read book Python Machine Learning written by Richard Moore and published by . This book was released on 2019-10-07 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: Buy the Paperback Version of this Book and get the Kindle Book version for FREE! Order Python Machine Learning: The Ultimate Guide for Beginners to Machine Learning with Python, Programming and Deep Learning, Artificial Intelligence, Neural Networks, and Data Science, NumPy, Scikit Learn, Pandas and Tensorflow now to learn all the basic concepts you need to know about machine learning and Python. The purpose of this book is to guide you step by step through the entire process of working with various machine learning algorithms. First you will learn the basics of working with Python in order to acquire the basic knowledge needed to understand machine learning. In each chapter you will learn a great deal of theory backed up by practical examples. Once you have the basics down, you will get to the core of machine learning algorithms and techniques. You will explore: Why machine learning is important and so popular with today's tech industry. The basics of working with Python. How to set up the development environment with the help of Python scientific distributions and libraries. How to preprocess your data and prepare it for training. How to work with the most important machine learning algorithms such as support vector machines and decision trees. The power of neural networks and how to work with feedforward, recurrent, and convolutional networks. Learning machine learning and working with training algorithms doesn't have to be a complex journey. Scroll up and click buy now so that Python Machine Learning can guide you step by step through the entire process. Learn using clear, simple, real-world examples and enjoy the power of Python and machine learning!

Download or read book Python Machine Learning from Scratch written by Daniel Nedal and published by Createspace Independent Publishing Platform. This book was released on 2017-07-24 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: ***BUY NOW (Will soon return to 20.59) ******Free eBook for customers who purchase the print book from Amazon*** Are you thinking of learning more about Machine Learning using Python? This book would seek to explain common terms and algorithms in an intuitive way. The author used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses. To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach which would lead to better mental representations. Step By Step Guide and Visual Illustrations and Examples This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using machine learning. Instead of tough math formulas, this book contains several graphs and images which detail all important Machine Learning concepts and their applications. Target Users The book designed for a variety of target audiences. The most suitable users would include: Anyone who is intrigued by how algorithms arrive at predictions but has no previous knowledge of the field. Software developers and engineers with a strong programming background but seeking to break into the field of machine learning. Seasoned professionals in the field of artificial intelligence and machine learning who desire a bird's eye view of current techniques and approaches. What's Inside This Book? Supervised Learning Algorithms Unsupervised Learning Algorithms Semi-supervised Learning Algorithms Reinforcement Learning Algorithms Overfitting and underfitting correctness The Bias-Variance Trade-off Feature Extraction and Selection A Regression Example: Predicting Boston Housing Prices Import Libraries: How to forecast and Predict Popular Classification Algorithms Introduction to K Nearest Neighbors Introduction to Support Vector Machine Example of Clustering Running K-means with Scikit-Learn Introduction to Deep Learning using TensorFlow Deep Learning Compared to Other Machine Learning Approaches Applications of Deep Learning How to run the Neural Network using TensorFlow Cases of Study with Real Data Sources & References Frequently Asked Questions Q: Is this book for me and do I need programming experience? A: If you want to smash Machine Learning from scratch, this book is for you. If you already wrote a few lines of code and recognize basic programming statements, you'll be OK. Q: Does this book include everything I need to become a Machine Learning expert? A: Unfortunately, no. This book is designed for readers taking their first steps in Machine Learning and further learning will be required beyond this book to master all aspects of Machine Learning. Q: Can I have a refund if this book is not fitted for me? A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email at [email protected]. If you need to see the quality of our job, AI Sciences Company offering you a free eBook in Machine Learning with Python written by the data scientist Alain Kaufmann at http: //aisciences.net/free-books/

Download or read book Python Machine Learning written by Anderson Coen and published by . This book was released on 2020-05-25 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Machine Learning Would you want to learn how to utilize Python to produce machine learning models, but you think it would be too complicated for you? Or maybe you like to automate simple stuff with your PC, but you do not know how to do it. As a novice, you might think programming is complicated. Understanding artificial intelligence coding could take several months. Not to mention that the chance of giving up before perfecting it could be high. Therefore, you could think of employing a professional developer to shorten the time if you have time to develop. That might look like a great solution, but it is surely very costly. You still have pay for the developer if he doesn't do the proper job you want. You know the best solution for this? The perfect solution is to follow a complete programming manual with hands-on projects as well as practical exercises. This book is structured as a course with six chapters. Inside the book, you will be able to go through a first section in which basic and fundamental notions of deep learning are mention, to get to the next chapters made to help you learn advanced coding insights needed to build training data sets for the development of successful machine learning models. In detail, you will learn: The Fundamentals of Machine Learning Machine-Learning Systems An Overview of Python for Machine Learning Understanding Python Libraries for Machine Learning Introducing Neural Networks and Deep Learning Practical Data Management What makes this book different? The majority of books available on the market take a brief look into machine learning, presenting some of the subjects but never going deep. This book is not one of those. Even if you are totally new to programming in 2020 or you're simply looking to widen your abilities as a programmer, this book is perfect for you! Well, stress no more! Buy this book and also learn all... and DOWNLOAD IT NOW!

Download or read book Python Machine Learning written by Ryan Turner and published by Publishing Factory . This book was released on 2020-04-12 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you a novice programmer who wants to learn Python Machine Learning? Are you worried about how to translate what you already know into Python? This book will help you overcome those problems. As machines get ever more complex and perform more and more tasks to free up our time, so it is that new ideas are developed to help us continually improve their speed and abilities. One of these is Python and in Python Machine Learning: The Ultimate Beginner's Guide to Learn Python Machine Learning Step by Step using Scikit-Learn and Tensorflow, you will discover information and advice on: • What machine learning is • The history of machine learning • Approaches to machine learning • Support vector machines • Machine learning and neural networks • The Internet of Things (IoT) • The future of machine learning • And more… This book has been written specifically for beginners and the simple, step by step instructions and plain language make it an ideal place to start for anyone who has a passing interest in this fascinating subject. Python really is an amazing system and can provide you with endless possibilities when you start learning about it. Get a copy of Python Machine Learning today and see where the future lies!

Download or read book Deep Learning with Python written by Chao Pan and published by Createspace Independent Publishing Platform. This book was released on 2016-06-14 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: ***** BUY NOW (will soon return to 24.77 $) *****Are you thinking of learning deep Learning using Python? (For Beginners Only) If you are looking for a beginners guide to learn deep learning, in just a few hours, this book is for you. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses.To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach, which would lead to better mental representations.Step-by-Step Guide and Visual Illustrations and ExamplesThis book and the accompanying examples, you would be well suited to tackle problems, which pique your interests using machine learning and deep learning models. Book Objectives This book will help you: Have an appreciation for deep learning and an understanding of their fundamental principles. Have an elementary grasp of deep learning concepts and algorithms. Have achieved a technical background in deep learning and neural networks using Python. Target UsersThe book designed for a variety of target audiences. Anyone who is intrigued by how algorithms arrive at predictions but has no previous knowledge of the field. Software developers and engineers with a strong programming background but seeking to break into the field of machine learning. Seasoned professionals in the field of artificial intelligence and deep learning who desire a bird's eye view of current techniques and approaches. What's Inside This Book? Introduction What is Artificial Intelligence, Machine Learning and Deep Learning? Mathematical Foundations of Deep Learning Understanding Machine Learning Models Evaluation of Machine Learning Models: Overfitting, Underfitting, Bias Variance Tradeoff Fully Connected Neural Networks Convolutional Neural Networks Recurrent Neural Networks Generative Adversarial Networks Deep Reinforcement Learning Introduction to Deep Neural Networks with Keras A First Look at Neural Networks in Keras Introduction to Pytorch The Pytorch Deep Learning Framework Your First Neural Network in Pytorch Deep Learning for Computer Vision Build a Convolutional Neural Network Deep Learning for Natural Language Processing Working with Sequential Data Build a Recurrent Neural Network Frequently Asked Questions Q: Is this book for me and do I need programming experience?A: if you want to smash Deep Learning from scratch, this book is for you. Little programming experience is required. If you already wrote a few lines of code and recognize basic programming statements, you'll be OK. Q: Can I have a refund if this book doesn't fit for me?A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email.***** MONEY BACK GUARANTEE BY AMAZON ***** Editorial Reviews"This is an excellent book, it is a very good introduction to deep learning and neural networks. The concepts and terminology are clearly explained. The book also points out several good locations on the internet where users can obtain more information. I was extremely happy with this book and I recommend it for all beginners" - Prof. Alain Simon, EDHEC Business School. Statistician and DataScientist.

Download or read book Python Machine Learning from Scratch written by Sebastian Dark and published by . This book was released on 2018-11-09 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, you will find the perfect balance between the information being very thorough and being able to understand it. Although tailored for beginners, it won't contain simple and easily accessible information.

Download or read book Python for Beginners 2021 written by Leo Sgarbi and published by Claudio Ametrano. This book was released on 2021-11-18 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python was developed in 1980s by Guido Van Rossum of Netherlands. Python was developed as an object-oriented language with an emphasis on simplicity, extensibility and flexibility. Python also comes with a large library of pre-built functionality for data science, statistical analysis and data visualizations which make this language very easy to learn and use. In this book we will focus on data science applications of Python with hands on examples that allow you to go from novice to expert in a short period of time! We will start with getting you set up with Python, introducing you to its data structures and libraries and then finally getting into the data science applications of this beautiful language. What you will find different about this book is the visual and hands on approach it takes to teaching Python. Since this book is directed at beginners, we will not drone on and on about complex concepts or make this book text heavy. Instead, we will take inspiration from the Zen of Python by Tim Peters.

Download or read book Deep Learning with Python written by Francois Chollet and published by Simon and Schuster. This book was released on 2017-11-30 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

Download or read book Python Machine Learning written by Ryan Turner and published by Publishing Factory . This book was released on 2020-04-18 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you need a general purpose, high level programming language? Do you want something that which focuses on readability and has less lines of codes than other programming languages? This book is one that provides that! Python is one of the best machine learning concepts currently on the market and it has seen a spike in popularity, mainly due to its simplicity when it comes to working with machine learning algorithms. Inside the pages of Python Machine Learning: The Ultimate Intermediate Guide to Learn Python Machine Learning Step by Step Using Scikit-learn and Tensorflow you will find easy to understand information which is perfect for those who want to take the next steps in their programming journey and includes: - The principles surrounding Python - Different types of networks so you can choose what works best for you - Features of the system - Real world feature engineering - Understanding the techniques of semi-supervised learning - And much more… If you already have some basic knowledge of Python, the various programming models and functional programming it supports, then this intermediate guide is perfect for expanding your knowledge base. Get your copy of this amazing book today and increase your Python skills now!

Download or read book Python for Data Science written by Daniel O'Reilly and published by . This book was released on 2020-11-23 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here's the Perfect Solution if You Want to Become the Master of Data Science and Learn Phyton Step-by-Step Would you like to: Learn a super competitive skill? Become irreplaceable in the future job market? Upgrade yourself to the ultimate data whizz? If so, then keep reading! Data science is one of the emerging technologies that is set to radically transform the job market. With applications in almost every industry, data science experts will have no shortage of great job offers. But, the whole field may seem a little intimidating if your background is not specific to data science. This book is here to guide you through the field of data science from the very beginning. You will learn the fundamental skills and tools to support your learning process. If you're a beginner, this is the book to help you easily understand the basics of data science. To understand data science, you also need a good understanding of how Python helps you design and implement these projects. This guidebook is going to explain how we can get all of this done. Here just a little preview of what you'll find inside this book: A thorough and simple explanation of data science and the way it works Basics of data science and fundamental skills you need to get started Data science libraries you need to learn to become a data whizz A blueprint for the most used frameworks for Python data science How to process and understand the data and design your own projects AND SO MUCH MORE! Even if you're an absolute beginner with little programming experience, you will find this book easy to follow and implement. This guide is your first step towards a successful data science career, so don't hesitate! Scroll Up, Click the "Buy Now with 1-Click", and Get Your Copy!

Download or read book Neural Network Projects with Python written by James Loy and published by Packt Publishing Ltd. This book was released on 2019-02-28 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key FeaturesDiscover neural network architectures (like CNN and LSTM) that are driving recent advancements in AIBuild expert neural networks in Python using popular libraries such as KerasIncludes projects such as object detection, face identification, sentiment analysis, and moreBook Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learnLearn various neural network architectures and its advancements in AIMaster deep learning in Python by building and training neural networkMaster neural networks for regression and classificationDiscover convolutional neural networks for image recognitionLearn sentiment analysis on textual data using Long Short-Term MemoryBuild and train a highly accurate facial recognition security systemWho this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.

Download or read book Machine Learning with Python written by Dan Phillips and published by Double M International Limited. This book was released on 2021-01-13 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you completely new to Python Programming or do you want to expand your knowledge in the incredible world of Machine Learning? If you would like to start Programming or learn about Machine Learning and its algorithms but may seem to be a struggle, don't worry! Thanks to this complete guide with practical projects and examples you will finally solve your problems! These 2 Books in 1 will teach you fundamental and advance information to master the easiest Programming language, Artificial Intelligence, Data Science and Machine Learning. Avoid the main mistakes everybody makes and stop waste your precious time and money in expensive online courses. This is what you will find in this step-by-step guide: Why Python and Machine Learning are a successful combo The secrets of the Machine Learning's Success The Best Trick and practice for Python Programming ... and that's not all! The Importance of Artificial Intelligence nowadays Solutions for Small Businesses Using Data Science The best Algorithms to use ...and much more!!! Take advantage of this Guide and discover this fantastic world! What are you waiting for? Press the Buy-Now button and get started!