Getting Started In Data Science

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Getting Started With Data Science

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Author : Murtaza Haider
language : en
Publisher: IBM Press
Release Date : 2015-12-14

Getting Started With Data Science written by Murtaza Haider and has been published by IBM Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-14 with Business & Economics categories.

Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy! Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now. Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing. You’ll master data science by answering fascinating questions, such as: • Are religious individuals more or less likely to have extramarital affairs? • Do attractive professors get better teaching evaluations? • Does the higher price of cigarettes deter smoking? • What determines housing prices more: lot size or the number of bedrooms? • How do teenagers and older people differ in the way they use social media? • Who is more likely to use online dating services? • Why do some purchase iPhones and others Blackberry devices? • Does the presence of children influence a family’s spending on alcohol? For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon.

Getting Started In Data Science

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Author : Ayodele Odubela
language : en
Publisher: fullyConnected Inc.
Release Date : 2020-12-01

Getting Started In Data Science written by Ayodele Odubela and has been published by fullyConnected Inc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-01 with Technology & Engineering categories.

Data Science is one of the "sexiest jobs of the 21st Century", but few resources are geared towards learners with no prior experience. Getting Started in Data Science simplifies the core of the concepts of Data Science and Machine Learning. This book includes perspectives of a Data Science from someone with a non-traditional route to a Data Science career. Getting Started in Data Science creatively weaves in ethical questions and asks readers to question the harm models can cause as they learn new concepts. Unlike many other books for beginners, this book covers bias and accountability in detail as well as career insight that informs readers of what expectations are in industry Data Science.

Getting Started With Data Science

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Author : Murtaza Haider
language : en
Publisher:
Release Date : 2016

Getting Started With Data Science written by Murtaza Haider and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Business enterprises categories.

Getting Started With Streamlit For Data Science

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Author : Tyler Richards
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-08-20

Getting Started With Streamlit For Data Science written by Tyler Richards 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 2021-08-20 with Computers categories.

Create, deploy, and test your Python applications, analyses, and models with ease using Streamlit Key Features Learn how to showcase machine learning models in a Streamlit application effectively and efficiently Become an expert Streamlit creator by getting hands-on with complex application creation Discover how Streamlit enables you to create and deploy apps effortlessly Book DescriptionStreamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time. You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps. By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.What you will learn Set up your first development environment and create a basic Streamlit app from scratch Explore methods for uploading, downloading, and manipulating data in Streamlit apps Create dynamic visualizations in Streamlit using built-in and imported Python libraries Discover strategies for creating and deploying machine learning models in Streamlit Use Streamlit sharing for one-click deployment Beautify Streamlit apps using themes, Streamlit Components, and Streamlit sidebar Implement best practices for prototyping your data science work with Streamlit Who this book is for This book is for data scientists and machine learning enthusiasts who want to create web apps using Streamlit. Whether you’re a junior data scientist looking to deploy your first machine learning project in Python to improve your resume or a senior data scientist who wants to use Streamlit to make convincing and dynamic data analyses, this book will help you get there! Prior knowledge of Python programming will assist with understanding the concepts covered.

Data Science 101

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Author : Andrew Park
language : en
Publisher: Andrew Park
Release Date : 2021-02-13

Data Science 101 written by Andrew Park and has been published by Andrew Park this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-13 with categories.

★ 55% OFF for Bookstores! NOW at $ 21,97 instead of $31.97! LAST DAYS! ★ Your Customers Will Never Stop To Use This Amazing Guide! Do you want to know how Data science helps in business? This book will discuss everything that we need to know when it comes to data science and how to complete the process of data science with Python. There are so many different parts that come together when we work on data science, but if you are able to put it all together, and work to really analyze the information that you have to beat out the competition, you will find that data science with Python can be the right move for you. We will explore how so many businesses will take the time to gather up information, usually from a variety of sources, and then will be unsure of what they should do with that information once they have collected it. We can then take a look at the data life cycle and how we can take that information, clean it off, analyze it, and come up with insights and predictions that help grow our business more than ever before. We will spend this time looking what Python is about, how to download the program on your chosen operating system, and some of the basics that come with coding in Python. This guidebook went through all of the steps that you need to know in order to get started with data science and some of the basic parts of the Python code. We can then put all of this together in order to create the right analytical algorithm that, once it is trained properly and tested with the right kinds of data, will work to make predictions, provide information, and even show us insights that were never possible before. And all that you need to do to get this information is to use the steps that we outline and discuss in this guidebook. There is a lot of buzz in the business world, no matter what industry it is, about machine learning, the Python language, and of course, data science, and being able to put these terms together and learn how they work can make a big difference in how well your business will do now and in the future. There are already a ton of companies out there who have been able to gain a competitive edge with data science and the various models and algorithms of Python that go with it, and you can as well. This book covers: What is Data Science? The Python Coding Language Some of the Basic Coding in Python The Best Python Libraries to Use with Data Science The Basics of Jupyter and Why We Should Use It Working with Anaconda in Python The Basics of the Pandas Library What is WinPython and How Can We Use It? Common Tasks to Do in Info Science Different Data Types to Work With The Future of Data Science and Where It Will Go from Here There are so many great ways that you can use the data you have been collecting for some time now and being able to complete the process of data visualization will ensure that you get it all done. When you are ready to get started with Python data science, make sure to check out this guidebook to learn how. There is so much that can come into play when we work with data science, and it is one of the best ways for a business to differentiate from the competition and actually see some results in the process. And the Python language is a great option to learn to help us analyze and create a model that works with the info that we have. When we are ready to learn more about data science, and how to use the Python coding language to go with it, make sure to check out this guidebook to help you get started. Buy it NOW and let your customers get addicted to this amazing book!

Python For Data Science For Dummies

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Author : John Paul Mueller
language : en
Publisher: John Wiley & Sons
Release Date : 2023-11-07

Python For Data Science For Dummies written by John Paul Mueller and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-07 with Computers categories.

Let Python do the heavy lifting for you as you analyze large datasets Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner’s guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights. This new edition is updated for the latest version of Python and includes current, relevant data examples. Get a firm background in the basics of Python coding for data analysis Learn about data science careers you can pursue with Python coding skills Integrate data analysis with multimedia and graphics Manage and organize data with cloud-based relational databases Python careers are on the rise. Grab this user-friendly Dummies guide and gain the programming skills you need to become a data pro.

Build A Career In Data Science

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Author : Emily Robinson
language : en
Publisher: Simon and Schuster
Release Date : 2020-03-06

Build A Career In Data Science written by Emily Robinson and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-06 with Computers categories.

Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on the job 10. Making an effective analysis 11. Deploying a model into production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder

Data Science From Scratch

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Author : Steven Cooper
language : en
Publisher: Roland Bind
Release Date : 2018-08-10

Data Science From Scratch written by Steven Cooper and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-10 with Computers categories.

★☆If you are looking to start a new career that is in high demand, then you need to continue reading!★☆​​​​​​​ Data scientists are changing the way big data is used in different institutions. Big data is everywhere, but without the right person to interpret it, it means nothing. So where do business find these people to help change their business? You could be that person! It has become a universal truth that businesses are full of data. With the use of big data, the US healthcare could reduce their health-care spending by $300 billion to $450 billion. It can easily be seen that the value of big data lies in the analysis and processing of that data, and that's where data science comes in. ★★ Grab your copy today and learn ★★ ♦ In depth information about what data science is and why it is important. ♦ The prerequisites you will need to get started in data science. ♦ What it means to be a data scientist. ♦ The roles that hacking and coding play in data science. ♦ The different coding languages that can be used in data science. ♦ Why python is so important. ♦ How to use linear algebra and statistics. ♦ The different applications for data science. ♦ How to work with the data through munging and cleaning ♦ And much more... The use of data science adds a lot of value to businesses, and we will continue to see the need for data scientists grow. As businesses and the internet change, so will data science. This means it's important to be flexible. When data science can reduce spending costs by billions of dollars in the healthcare industry, why wait to jump in? If you want to get started in a new, ever growing, career, don't wait any longer. Scroll up and click the buy now button to get this book today!

Data Science Without Makeup

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Author : Mikhail Zhilkin
language : en
Publisher: CRC Press
Release Date : 2021-11-01

Data Science Without Makeup written by Mikhail Zhilkin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-01 with Computers categories.

Mikhail Zhilkin, a data scientist who has worked on projects ranging from Candy Crush games to Premier League football players’ physical performance, shares his strong views on some of the best and, more importantly, worst practices in data analytics and business intelligence. Why data science is hard, what pitfalls analysts and decision-makers fall into, and what everyone involved can do to give themselves a fighting chance—the book examines these and other questions with the skepticism of someone who has seen the sausage being made. Honest and direct, full of examples from real life, Data Science Without Makeup: A Guidebook for End-Users, Analysts and Managers will be of great interest to people who aspire to work with data, people who already work with data, and people who work with people who work with data—from students to professional researchers and from early-career to seasoned professionals. Mikhail Zhilkin is a data scientist at Arsenal FC. He has previously worked on the popular Candy Crush mobile games and in sports betting.

Advanced Natural Language Processing With Tensorflow 2

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Author : Ashish Bansal
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-02-04

Advanced Natural Language Processing With Tensorflow 2 written by Ashish Bansal 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 2021-02-04 with Computers categories.

One-stop solution for NLP practitioners, ML developers, and data scientists to build effective NLP systems that can perform real-world complicated tasks Key FeaturesApply deep learning algorithms and techniques such as BiLSTMS, CRFs, BPE and more using TensorFlow 2Explore applications like text generation, summarization, weakly supervised labelling and moreRead cutting edge material with seminal papers provided in the GitHub repository with full working codeBook Description Recently, there have been tremendous advances in NLP, and we are now moving from research labs into practical applications. This book comes with a perfect blend of both the theoretical and practical aspects of trending and complex NLP techniques. The book is focused on innovative applications in the field of NLP, language generation, and dialogue systems. It helps you apply the concepts of pre-processing text using techniques such as tokenization, parts of speech tagging, and lemmatization using popular libraries such as Stanford NLP and SpaCy. You will build Named Entity Recognition (NER) from scratch using Conditional Random Fields and Viterbi Decoding on top of RNNs. The book covers key emerging areas such as generating text for use in sentence completion and text summarization, bridging images and text by generating captions for images, and managing dialogue aspects of chatbots. You will learn how to apply transfer learning and fine-tuning using TensorFlow 2. Further, it covers practical techniques that can simplify the labelling of textual data. The book also has a working code that is adaptable to your use cases for each tech piece. By the end of the book, you will have an advanced knowledge of the tools, techniques and deep learning architecture used to solve complex NLP problems. What you will learnGrasp important pre-steps in building NLP applications like POS taggingUse transfer and weakly supervised learning using libraries like SnorkelDo sentiment analysis using BERTApply encoder-decoder NN architectures and beam search for summarizing textsUse Transformer models with attention to bring images and text togetherBuild apps that generate captions and answer questions about images using custom TransformersUse advanced TensorFlow techniques like learning rate annealing, custom layers, and custom loss functions to build the latest DeepNLP modelsWho this book is for This is not an introductory book and assumes the reader is familiar with basics of NLP and has fundamental Python skills, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra. The readers who can benefit the most from this book include intermediate ML developers who are familiar with the basics of supervised learning and deep learning techniques and professionals who already use TensorFlow/Python for purposes such as data science, ML, research, analysis, etc.