| Uploader: | Belovrus |
| Date Added: | 29.08.2015 |
| File Size: | 32.64 Mb |
| Operating Systems: | Windows NT/2000/XP/2003/2003/7/8/10 MacOS 10/X |
| Downloads: | 22629 |
| Price: | Free* [*Free Regsitration Required] |
Python Machine Learning Cookbook - Second Edition
File type: PDF €|€ pages | File size: Mb I think that Python Machine Learning Cookbook are great because they are so attention holding, I mean you know how people describe Python Machine Learning Cookbook By Prateek Joshi good books by saying they cant stop reading them, well, I really could not stop reading. It is yet again another. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking. The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis. Python Machine Learning Cookbook PDF Free Download. Report Link. Issue: *.
Machine learning with python cookbook pdf download
Author by : Prateek Joshi Languange : en Publisher by : Machine learning with python cookbook pdf download Publishing Ltd Format Available : PDF, ePub, Mobi Total Read : 91 Total Download : File Size : 54,6 Mb Description : recipes that teach you how to perform various machine learning tasks in the real world About This Book Understand which algorithms to use in a given context with the help of this exciting recipe-based guide Learn about perceptrons and see how they are used to build neural networks Stuck while making sense of images, text, speech, and real estate?
This guide will come to your rescue, showing you how to perform machine learning for each one of these using various techniques Who This Book Is For This book is for Python programmers who are looking to use machine-learning algorithms to create real-world applications.
This book is friendly to Python beginners, but familiarity with Python programming would certainly be useful to machine learning with python cookbook pdf download around with the code.
What You Will Learn Explore classification algorithms and machine learning with python cookbook pdf download them to the income bracket estimation problem Use predictive modeling and apply it to real-world problems Understand how to perform market segmentation using unsupervised learning Explore data visualization techniques to interact with your data in diverse ways Find out how to build a recommendation engine Understand how to interact with text data and build models to analyze it Work with speech machine learning with python cookbook pdf download and recognize spoken words using Hidden Markov Models Analyze stock market data using Conditional Random Fields Work with image data and build systems for image recognition and biometric face recognition Grasp how to use deep neural networks to build an optical character recognition system In Detail Machine learning is becoming increasingly pervasive in the modern data-driven world.
It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. With this book, you will learn how to perform various machine learning tasks in different environments. We'll start by exploring a range of real-life scenarios where machine learning can be used, and look at various building blocks. Throughout the book, you'll use a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms.
You'll discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning. We also cover a range of regression techniques, classification algorithms, predictive modeling, data visualization techniques, recommendation engines, and more with the help of real-world examples. Style and approach You will explore various real-life scenarios in this book where machine learning can be used, and learn about different building blocks of machine learning using independent recipes in the book.
Author by : Giuseppe Ciaburro Languange : en Publisher by : Packt Publishing Ltd Format Available : PDF, ePub, Mobi Total Read : 41 Total Download : File Size : 44,8 Mb Description : Discover powerful ways to effectively solve real-world machine learning problems machine learning with python cookbook pdf download key libraries including scikit-learn, TensorFlow, and PyTorch Key Features Learn and implement machine learning algorithms in a variety of real-life scenarios Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques Machine learning with python cookbook pdf download easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks.
With the help of over recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, machine learning with python cookbook pdf download, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems.
Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples.
What you will learn Use predictive modeling and apply it to real-world problems Explore data visualization techniques to interact with your data Learn how to build a recommendation engine Understand how to interact with text data and build models to analyze it Work with speech data and recognize spoken words using Hidden Markov Models Get well versed with reinforcement learning, automated ML, and transfer learning Work with image data and build systems for image recognition and biometric face recognition Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms.
If you are facing challenges at work and want ready-to-use machine learning with python cookbook pdf download solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need.
Familiarity with Python programming and machine learning concepts will be useful. Thorough understanding of the machine learning concepts and Python libraries such as NumPy, SciPy and scikit-learn is expected. Additionally, basic knowledge in linear algebra and calculus is desired. For many applications, machine learning with python cookbook pdf download, deep learning has proven to outperform humans by making faster and more accurate predictions.
This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, machine learning with python cookbook pdf download, PyTorch, Keras and CNTK is provided.
The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies.
The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios. Style and approach Unique blend of independent recipes arranged in the most logical manner. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before, machine learning with python cookbook pdf download.
With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more.
Through real-world examples, machine learning with python cookbook pdf download, you will get hands-on experience with linear regression techniques with TensorFlow.
Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.
What you will learn Become familiar with the basic features of the TensorFlow library Get to know Linear Regression techniques with TensorFlow Learn SVMs with hands-on recipes Implement neural networks to improve predictive modeling Apply NLP and sentiment analysis to your data Master CNN and RNN through practical recipes Implement the gradient boosted random forest to predict housing prices Take TensorFlow into production Who this book is for If you are a data scientist or a machine learning engineer with some knowledge of linear algebra, statistics, and machine learning, this book is for you.
If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading pages and pages of material, this book is for you. Some background in Python programming is assumed.
Author by : Giuseppe Ciaburro Languange : en Publisher by : Format Available : PDF, machine learning with python cookbook pdf download, ePub, Mobi Total Read : 51 Total Download : File Size : 48,7 Mb Description : Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features Learn and implement machine learning algorithms in a variety of real-life scenarios Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks.
If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is w Author by : Rajdeep Dua Languange : en Publisher by : Packt Publishing Ltd Format Available : PDF, ePub, Mobi Total Machine learning with python cookbook pdf download : 80 Total Download : File Size : 53,9 Mb Description : Leverage the power of deep learning and Keras to develop smarter and more efficient data models Key Features Understand different neural networks and their implementation using Keras Explore recipes for training and fine-tuning your neural network models Put your deep learning knowledge to practice with real-world use-cases, tips, and tricks Book Description Keras has quickly emerged as a popular deep learning library.
Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy.
The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow.
From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide.
In addition to this, you will learn how to train these models for real-world image and language processing tasks. By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning What you will learn Install and configure Keras in TensorFlow Master neural network programming using the Keras library Understand the different Keras layers Use Keras to implement simple feed-forward neural networks, CNNs and RNNs Work with various datasets and models used for image and text classification Develop text summarization and reinforcement learning models using Keras Who this book is for Keras Deep Learning Cookbook is for you if you are a data scientist or machine learning expert who wants to find practical solutions to common problems encountered while training deep learning models.
A basic understanding of Python and some experience in machine learning and neural networks is required for this book. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, machine learning with python cookbook pdf download, you can insert, combine, or adapt the code to help construct your application.
Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. Author by : Emmanuel Tsukerman Languange : en Publisher by : Packt Publishing Ltd Format Available : PDF, ePub, Mobi Total Read : 10 Total Download : File Size : 41,6 Mb Description : Learn how to apply modern AI to create powerful cybersecurity solutions for malware, pentesting, social engineering, data privacy, and intrusion detection Key Features Manage data of varying complexity to protect your system using the Python ecosystem Apply ML to pentesting, malware, data privacy, intrusion detection system IDS and social engineering Automate your daily workflow by addressing various security challenges using the recipes covered in the book Book Description Organizations today face a major threat in terms of cybersecurity, from malicious URLs to credential reuse, and having robust security systems can make all the difference.
With this book, you'll learn how to use Python libraries such as TensorFlow and scikit-learn to implement the latest artificial intelligence AI techniques and handle challenges faced by cybersecurity researchers. You'll begin by exploring various machine learning ML techniques and tips for setting up a secure lab environment.
Next, you'll implement key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book will guide you through constructing classifiers and features for malware, which you'll train and test on real samples. As you progress, you'll build self-learning, reliant systems to handle cybersecurity tasks such as identifying malicious URLs, spam email detection, intrusion detection, network protection, and tracking user and process behavior.
Later, you'll apply generative adversarial networks GANs and autoencoders to advanced security tasks. Finally, you'll delve into secure and private AI to protect the privacy rights of consumers using your ML models.
By the end of machine learning with python cookbook pdf download book, you'll have the skills you need to tackle real-world problems faced in the cybersecurity domain using a recipe-based approach.
What you will learn Learn how to build malware classifiers to detect suspicious activities Apply ML to generate custom malware to pentest your security Use ML algorithms with complex datasets to implement cybersecurity concepts Create neural networks to identify fake videos and images Secure your organization from one of the most popular threats — insider threats Defend against zero-day threats by constructing an anomaly detection system Detect web vulnerabilities effectively by combining Metasploit and ML Understand how to train a model without exposing the training data Who this book is for This book is for cybersecurity professionals and security researchers who are looking to implement the latest machine learning techniques to boost computer security, and gain insights into securing an organization using red and blue team ML.
This recipe-based book will also be useful for data scientists and machine learning developers who want to experiment with smart techniques in the cybersecurity domain. Working knowledge of Python programming and familiarity with cybersecurity fundamentals will help you get the most out of this book. Author by machine learning with python cookbook pdf download Dipayan Sarkar Languange : en Publisher by : Packt Publishing Ltd Format Available : PDF, ePub, Mobi Total Read : 22 Total Download : File Size : 45,6 Mb Description : Implement machine learning algorithms to build ensemble models using Keras, H2O, machine learning with python cookbook pdf download, Scikit-Learn, Machine learning with python cookbook pdf download and more Key Features Apply popular machine learning algorithms using a recipe-based approach Implement boosting, bagging, and stacking ensemble methods to improve machine learning models Discover real-world ensemble applications and encounter complex challenges in Kaggle competitions Book Description Ensemble modeling is an approach used to improve the performance of machine learning models.
It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking. The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis.
You'll then learn to implement tasks related to statistical and machine learning algorithms to understand the ensemble of multiple heterogeneous algorithms. It will also ensure that you don't miss out on key topics, such as like resampling methods. The book will highlight how these ensemble methods use multiple models to improve machine learning results, as compared to a single model.
In the concluding chapters, you'll delve into advanced ensemble models using neural networks, natural language processing, and more. By the end of this book, you'll be able to harness ensemble techniques and the working mechanisms of machine learning algorithms to build intelligent models using individual recipes. What you will learn Understand how to use machine learning algorithms for regression and classification problems Implement ensemble techniques such as averaging, machine learning with python cookbook pdf download, weighted averaging, and max-voting Get to grips with advanced ensemble methods, such as bootstrapping, bagging, and stacking Use Random Forest for tasks such as classification and regression Implement an ensemble of homogeneous and heterogeneous machine learning algorithms Learn and implement various boosting techniques, such as AdaBoost, Gradient Boosting Machine, and XGBoost Who this book is for This book is designed for data scientists, machine learning developers, and deep learning enthusiasts who want to delve into machine learning algorithms to build powerful ensemble models.
Working knowledge of Python programming and basic statistics is a must to help you grasp the concepts in the book. Recent Search Terms forest of ruin kelley armstrong pdf keep me in mind pdf changing your world textbook pdf the demon king pdf download Leading People the Black Belt Way: Conquering the Five Core Problems Facing Leaders Todaypdf red hills of home-chenjerai hove pdf poverty pdf download lost book of king og pdf the innovators pdf by billington first 90 days book pdf download.
Top 5 Machine Learning Books
, time: 4:28Machine learning with python cookbook pdf download
Download machine learning with python cookbook by chris albon pdf or read machine learning with python cookbook by chris albon pdf online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get machine learning with python cookbook by chris albon pdf book now. This site is like a library, Use search box in the widget to get ebook that you want. Chapter 1: Getting Started with Python Machine Learning 7 Machine learning and Python – the dream team 8 What the book will teach you (and what it will not) 9 What to do when you are stuck 10 Getting started 11 Introduction to NumPy, SciPy, and Matplotlib 12 Installing Python 12 Chewing data efficiently with NumPy and intelligently with SciPy Dropbox TensorFlow Machine Learning Cookbook.
No comments:
Post a Comment