Data Science From Scratch 2nd Edition

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Data Science From Scratch

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Author : Joel Grus
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-04-12

Data Science From Scratch written by Joel Grus and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-12 with Computers categories.

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. With this updated second edition, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.

Data Science From Scratch 2nd Edition

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Author : Joel Grus
language : en
Publisher:
Release Date : 2019

Data Science From Scratch 2nd Edition written by Joel Grus and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the discipline without actually understanding data science. With this updated second edition, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today's messy glut of data holds answers to questions no one's even thought to ask. This book provides you with the know-how to dig those answers out.

Data Science From Scratch

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Author : Joel Grus
language : en
Publisher:
Release Date : 2015

Data Science From Scratch written by Joel Grus and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Data structures (Computer science) categories.

Data Science At The Command Line

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Author : Jeroen Janssens
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-08-17

Data Science At The Command Line written by Jeroen Janssens and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-17 with Computers categories.

This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools--useful whether you work with Windows, macOS, or Linux. You'll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you're comfortable processing data with Python or R, you'll learn how to greatly improve your data science workflow by leveraging the command line's power. This book is ideal for data scientists, analysts, engineers, system administrators, and researchers. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on text, CSV, HTML, XML, and JSON files Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow Create your own tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines Model data with dimensionality reduction, regression, and classification algorithms Leverage the command line from Python, Jupyter, R, RStudio, and Apache Spark

Data Science For Librarians

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Author : Yunfei Du
language : en
Publisher: Bloomsbury Publishing USA
Release Date : 2020-03-26

Data Science For Librarians written by Yunfei Du and has been published by Bloomsbury Publishing USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-26 with Language Arts & Disciplines categories.

This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries. Data Science for Librarians introduces data science to students and practitioners in library services. Writing for academic, public, and school library managers; library science students; and library and information science educators, authors Yunfei Du and Hammad Rauf Khan provide a thorough overview of conceptual and practical tools for data librarian practice. Partially due to how quickly data science evolves, libraries have yet to recognize core competencies and skills required to perform the job duties of a data librarian. As society transitions from the information age into the era of big data, librarians and information professionals require new knowledge and skills to stay current and take on new job roles, such as data librarianship. Such skills as data curation, research data management, statistical analysis, business analytics, visualization, smart city data, and learning analytics are relevant in library services today and will become increasingly so in the near future. This text serves as a tool for library and information science students and educators working on data science curriculum design.

Hands On Machine Learning With Scikit Learn Keras And Tensorflow

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Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-10-04

Hands On Machine Learning With Scikit Learn Keras And Tensorflow written by Aurélien Géron and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-04 with Computers categories.

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use Scikit-learn to track an example ML project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning

Hands On Machine Learning With Scikit Learn And Pytorch

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Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-10-22

Hands On Machine Learning With Scikit Learn And Pytorch written by Aurélien Géron and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-22 with Computers categories.

The potential of machine learning today is extraordinary, yet many aspiring developers and tech professionals find themselves daunted by its complexity. Whether you're looking to enhance your skill set and apply machine learning to real-world projects or are simply curious about how AI systems function, this book is your jumping-off place. With an approachable yet deeply informative style, author Aurélien Géron delivers the ultimate introductory guide to machine learning and deep learning. Drawing on the Hugging Face ecosystem, with a focus on clear explanations and real-world examples, the book takes you through cutting-edge tools like Scikit-Learn and PyTorch—from basic regression techniques to advanced neural networks. Whether you're a student, professional, or hobbyist, you'll gain the skills to build intelligent systems. Understand ML basics, including concepts like overfitting and hyperparameter tuning Complete an end-to-end ML project using scikit-Learn, covering everything from data exploration to model evaluation Learn techniques for unsupervised learning, such as clustering and anomaly detection Build advanced architectures like transformers and diffusion models with PyTorch Harness the power of pretrained models—including LLMs—and learn to fine-tune them Train autonomous agents using reinforcement learning

Kubeflow For Machine Learning

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Author : Trevor Grant
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-10-13

Kubeflow For Machine Learning written by Trevor Grant and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-13 with Computers categories.

If you're training a machine learning model but aren't sure how to put it into production, this book will get you there. Kubeflow provides a collection of cloud native tools for different stages of a model's lifecycle, from data exploration, feature preparation, and model training to model serving. This guide helps data scientists build production-grade machine learning implementations with Kubeflow and shows data engineers how to make models scalable and reliable. Using examples throughout the book, authors Holden Karau, Trevor Grant, Ilan Filonenko, Richard Liu, and Boris Lublinsky explain how to use Kubeflow to train and serve your machine learning models on top of Kubernetes in the cloud or in a development environment on-premises. Understand Kubeflow's design, core components, and the problems it solves Understand the differences between Kubeflow on different cluster types Train models using Kubeflow with popular tools including Scikit-learn, TensorFlow, and Apache Spark Keep your model up to date with Kubeflow Pipelines Understand how to capture model training metadata Explore how to extend Kubeflow with additional open source tools Use hyperparameter tuning for training Learn how to serve your model in production

Data Science From Scratch

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Author : G S Collins
language : en
Publisher:
Release Date : 2020-01-13

Data Science From Scratch written by G S Collins and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-13 with categories.

Become the master of machine learning with this powerful guide. Do you want to know more about neural networks? Have you heard of machine learning, but you're not sure where to begin? Written with the beginner in mind, this detailed guide breaks down everything you need to know about deep and machine learning in a simple, easy-to-understand way. Machine learning is a fascinating and ever-growing field, and its development will shape our futures. Now, you can understand what makes this topic so powerful no matter your level of experience. Using the popular and much-loved programming language Python, inside this comprehensive guide, you will: Learn How to Get Started with Jupyter Notebooks Understand Python Using Various Data Structures Perform Object Oriented Programming Using Python Use The Most Common Libraries Including Numpy, Matplotlib, and Pandas Learn and Recap on The Basics of Linear Algebra and Statistics Comprehend Machine Learning Algorithms Like Linear Regression, Logistic Regression, K-nearest neighbors and Decision Trees Discover Deep Learning Concepts Like Convolutional Neural Networks and Recurrent Neural Networks Implement CNNs and RNNs using Keras Deep Learning Framework And More! With a wide variety of vital topics, this book is your all-in-one ticket to understanding machine learning. Plus, you'll also learn bonus content, such as Generative Adversarial Network (GAN) models and why they're so important. With simple explanations designed to get you comfortable with the maths and statistics behind machine learning, this book is perfect for both the novice and the pro! So what are you waiting for? Buy now to begin your machine learning journey today!

Data Science From Scratch With Python

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Author : Peter Morgan
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-08-21

Data Science From Scratch With Python written by Peter Morgan and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-21 with Data mining categories.

***** BUY NOW (will soon return to 24.77 $) ***** MONEY BACK GUARANTEE BY AMAZON (See Below FAQ) *****Are you thinking of learning data science from scratch using Python? (For Beginners)If you are looking for a complete step-by-step guide to data science using Python from scratch, this book is for you. After his great success with his first book "Data Analysis from Scratch with Python," Peter Morgan publishes his second book focusing now in data science and machine learning. It is considered by practitioners as the easiest guide ever written in this domain. 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. Readers are advised to adopt a hands on approach, which would lead to better mental representations. Step by Step Guide and Visual Illustrations and ExamplesThe Book give complete instructions for manipulating, processing, cleaning, modeling and crunching datasets in Python. This is a hands-on guide with practical case studies of data analysis problems effectively. You will learn, pandas, NumPy, IPython, and Jupiter in the Process. Target Users Beginners who want to approach data science, but are too afraid of complex math to start Newbies in computer science techniques and data science Professors, lecturers or tutors who are looking to find better ways to explain the content to their students in the simplest and easiest way Students and academicians, especially those focusing on data science What's Inside This Book? Part 1: Data Science Fundamentals, Concepts and Algorithms Introduction Statistics Probability Bayes' Theorem and Naïve Bayes Algorithm Asking the Right Question Data Acquisition Data Preparation Data Exploration Data Modelling Data Presentation Supervised Learning Algorithms Unsupervised Learning Algorithms Semi-supervised Learning Algorithms Reinforcement Learning Algorithms Overfitting and Underfitting The Bias-Variance Trade-off Feature Extraction and Selection Part 2: Data Science in Practice Overview of Python Programming Language Python Data Science Tools Jupyter Notebook Numerical Python (Numpy) Pandas Scientific Python (Scipy) Matplotlib Scikit-Learn K-Nearest Neighbors Naive Bayes Simple and Multiple Linear Regression Logistic Regression GLM models Decision Trees and Random forest Perceptrons Backpropagation Clustering Natural Language Processing Frequently Asked Questions Q: Does this book include everything I need to become a data science expert?A: Unfortunately, no. This book is designed for readers taking their first steps in data science and machine learning using Python and further learning will be required beyond this book to master all aspects. 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.***** MONEY BACK GUARANTEE BY AMAZON ***** Editorial Reviews "This is a fantastic book on Python-based data science, data analysis, machine learning, Reinforcement learning and deep learning. As a data scientist with more than 10 years, Peter has had long experience in data science and give in this book the key elements.." - Lei Xia, Data Scientist Expert at Facebook