Data Science Fundamentals For Python And Mongodb
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Data Science Fundamentals For Python And Mongodb
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Author : David Paper
language : en
Publisher: Apress
Release Date : 2018-05-10
Data Science Fundamentals For Python And Mongodb written by David Paper and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-10 with Computers categories.
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate. The book is a necessary precursor to applying and implementing machine learning algorithms. The book is self-contained. All of the math, statistics, stochastic, and programming skills required to master the content are covered. In-depth knowledge of object-oriented programming isn’t required because complete examples are provided and explained. Data Science Fundamentals with Python and MongoDB is an excellent starting point for those interested in pursuing a career in data science. Like any science, the fundamentals of data science are a prerequisite to competency. Without proficiency in mathematics, statistics, data manipulation, and coding, the path to success is “rocky” at best. The coding examples in this book are concise, accurate, and complete, and perfectly complement the data science concepts introduced. What You'll Learn Prepare for a career in data science Work with complex data structures in Python Simulate with Monte Carlo and Stochastic algorithms Apply linear algebra using vectors and matrices Utilize complex algorithms such as gradient descent and principal component analysis Wrangle, cleanse, visualize, and problem solve with data Use MongoDB and JSON to work with data Who This Book Is For The novice yearning to break into the data science world, and the enthusiast looking to enrich, deepen, and develop data science skills through mastering the underlying fundamentalsthat are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming will make learning easier.
Mongodb And Python
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Author : Niall O'Higgins
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2011-09-23
Mongodb And Python written by Niall O'Higgins 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 2011-09-23 with Computers categories.
Learn how to leverage MongoDB with your Python applications, using the hands-on recipes in this book. You get complete code samples for tasks such as making fast geo queries for location-based apps, efficiently indexing your user documents for social-graph lookups, and many other scenarios. This guide explains the basics of the document-oriented database and shows you how to set up a Python environment with it. Learn how to read and write to MongoDB, apply idiomatic MongoDB and Python patterns, and use the database with several popular Python web frameworks. You’ll discover how to model your data, write effective queries, and avoid concurrency problems such as race conditions and deadlocks. The recipes will help you: Read, write, count, and sort documents in a MongoDB collection Learn how to use the rich MongoDB query language Maintain data integrity in replicated/distributed MongoDB environments Use embedding to efficiently model your data without joins Code defensively to avoid keyerrors and other bugs Apply atomic operations to update game scores, billing systems, and more with the fast accounting pattern Use MongoDB with the Pylons 1.x, Django, and Pyramid web frameworks
Hands On Scikit Learn For Machine Learning Applications
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Author : David Paper
language : en
Publisher: Apress
Release Date : 2019-11-16
Hands On Scikit Learn For Machine Learning Applications written by David Paper and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-16 with Mathematics categories.
Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised and unsupervised machine learning algorithms. Care is taken to walk you through the principles of machine learning through clear examples written in Python that you can try out and experiment with at home on your own machine. All applied math and programming skills required to master the content are covered in this book. In-depth knowledge of object-oriented programming is not required as working and complete examples are provided and explained. Coding examples are in-depth and complex when necessary. They are also concise, accurate, and complete, and complement the machine learning concepts introduced. Working the examples helps to build the skills necessary to understand and apply complexmachine learning algorithms. Hands-on Scikit-Learn for Machine Learning Applications is an excellent starting point for those pursuing a career in machine learning. Students of this book will learn the fundamentals that are a prerequisite to competency. Readers will be exposed to the Anaconda distribution of Python that is designed specifically for data science professionals, and will build skills in the popular Scikit-Learn library that underlies many machine learning applications in the world of Python. What You'll Learn Work with simple and complex datasets common to Scikit-Learn Manipulate data into vectors and matrices for algorithmic processing Become familiar with the Anaconda distribution used in data science Apply machine learning with Classifiers, Regressors, and Dimensionality Reduction Tune algorithms and find the best algorithms for each dataset Load data from and save to CSV, JSON, Numpy, and Pandas formats Who This Book Is For The aspiring data scientist yearning to break into machine learning through mastering the underlying fundamentals that are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming and very basic applied linear algebra will make learning easier, although anyone can benefit from this book.
Fundamentals Of Data Science
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Author : Mr.Desidi Narsimha Reddy
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-09-05
Fundamentals Of Data Science written by Mr.Desidi Narsimha Reddy and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-05 with Computers categories.
Mr.Desidi Narsimha Reddy, Data Consultant (Data Governance, Data Analytics: Enterprise Performance Management, AI & ML), Soniks consulting LLC, 101 E Park Blvd Suite 600, Plano, TX 75074, United States. Lova Naga Babu Ramisetti, EPM Consultant, Department of Information Technology, MiniSoft Empowering Techonolgy, 10333 Harwin Dr. #375e, Houston, TX 77036, USA. Mr.Harikrishna Pathipati, EPM Manager, Department of Information Technology, ITG Technologies, 10998 S Wilcrest Dr, Houston, TX 77099, USA.
Business Analytics For Professionals
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Author : Alp Ustundag
language : en
Publisher: Springer Nature
Release Date : 2022-05-09
Business Analytics For Professionals written by Alp Ustundag and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-09 with Business & Economics categories.
This book explains concepts and techniques for business analytics and demonstrate them on real life applications for managers and practitioners. It illustrates how machine learning and optimization techniques can be used to implement intelligent business automation systems. The book examines business problems concerning supply chain, marketing & CRM, financial, manufacturing and human resources functions and supplies solutions in Python.
Collecting Lives
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Author : Elizabeth Rodrigues
language : en
Publisher: University of Michigan Press
Release Date : 2022-05-16
Collecting Lives written by Elizabeth Rodrigues and has been published by University of Michigan Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-16 with Literary Criticism categories.
On a near-daily basis, data is being used to narrate our lives. Categorizing algorithms draw from amassed personal data to assign narrative destinies to individuals at crucial junctures, simultaneously predicting and shaping the paths of our lives. Data is commonly assumed to bring us closer to objectivity, but the narrative paths these algorithms assign seem, more often than not, to replicate biases about who an individual is and could become. While the social effects of such algorithmic logics seem new and newly urgent to consider, Collecting Lives looks to the late nineteenth and early twentieth century US to provide an instructive prehistory to the underlying question of the relationship between data, life, and narrative. Rodrigues contextualizes the application of data collection to human selfhood in the late nineteenth and early twentieth century US in order to uncover a modernist aesthetic of data that offers an alternative to the algorithmic logic pervading our sense of data’s revelatory potential. Examining the work of W. E. B. Du Bois, Henry Adams, Gertrude Stein, and Ida B. Wells-Barnett, Rodrigues asks how each of these authors draw from their work in sociology, history, psychology, and journalism to formulate a critical data aesthetic as they attempt to answer questions of identity around race, gender, and nation both in their research and their life writing. These data-driven modernists not only tell different life stories with data, they tell life stories differently because of data.
Data Science Bookcamp
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Author : Leonard Apeltsin
language : en
Publisher: Simon and Schuster
Release Date : 2021-12-07
Data Science Bookcamp written by Leonard Apeltsin 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 2021-12-07 with Computers categories.
Learn data science with Python by building five real-world projects! Experiment with card game predictions, tracking disease outbreaks, and more, as you build a flexible and intuitive understanding of data science. In Data Science Bookcamp you will learn: - Techniques for computing and plotting probabilities - Statistical analysis using Scipy - How to organize datasets with clustering algorithms - How to visualize complex multi-variable datasets - How to train a decision tree machine learning algorithm In Data Science Bookcamp you’ll test and build your knowledge of Python with the kind of open-ended problems that professional data scientists work on every day. Downloadable data sets and thoroughly-explained solutions help you lock in what you’ve learned, building your confidence and making you ready for an exciting new data science career. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology A data science project has a lot of moving parts, and it takes practice and skill to get all the code, algorithms, datasets, formats, and visualizations working together harmoniously. This unique book guides you through five realistic projects, including tracking disease outbreaks from news headlines, analyzing social networks, and finding relevant patterns in ad click data. About the book Data Science Bookcamp doesn’t stop with surface-level theory and toy examples. As you work through each project, you’ll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don’t quite fit the model you’re building. You’ll appreciate the detailed setup instructions and the fully explained solutions that highlight common failure points. In the end, you’ll be confident in your skills because you can see the results. What's inside - Web scraping - Organize datasets with clustering algorithms - Visualize complex multi-variable datasets - Train a decision tree machine learning algorithm About the reader For readers who know the basics of Python. No prior data science or machine learning skills required. About the author Leonard Apeltsin is the Head of Data Science at Anomaly, where his team applies advanced analytics to uncover healthcare fraud, waste, and abuse. Table of Contents CASE STUDY 1 FINDING THE WINNING STRATEGY IN A CARD GAME 1 Computing probabilities using Python 2 Plotting probabilities using Matplotlib 3 Running random simulations in NumPy 4 Case study 1 solution CASE STUDY 2 ASSESSING ONLINE AD CLICKS FOR SIGNIFICANCE 5 Basic probability and statistical analysis using SciPy 6 Making predictions using the central limit theorem and SciPy 7 Statistical hypothesis testing 8 Analyzing tables using Pandas 9 Case study 2 solution CASE STUDY 3 TRACKING DISEASE OUTBREAKS USING NEWS HEADLINES 10 Clustering data into groups 11 Geographic location visualization and analysis 12 Case study 3 solution CASE STUDY 4 USING ONLINE JOB POSTINGS TO IMPROVE YOUR DATA SCIENCE RESUME 13 Measuring text similarities 14 Dimension reduction of matrix data 15 NLP analysis of large text datasets 16 Extracting text from web pages 17 Case study 4 solution CASE STUDY 5 PREDICTING FUTURE FRIENDSHIPS FROM SOCIAL NETWORK DATA 18 An introduction to graph theory and network analysis 19 Dynamic graph theory techniques for node ranking and social network analysis 20 Network-driven supervised machine learning 21 Training linear classifiers with logistic regression 22 Training nonlinear classifiers with decision tree techniques 23 Case study 5 solution
Data Science Fundamentals And Practical Approaches
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Author : Dr. Gypsy Nandi
language : en
Publisher: BPB Publications
Release Date : 2020-06-02
Data Science Fundamentals And Practical Approaches written by Dr. Gypsy Nandi and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-02 with Computers categories.
Learn how to process and analysis data using PythonÊ KEY FEATURESÊ - The book has theories explained elaborately along with Python code and corresponding output to support the theoretical explanations. The Python codes are provided with step-by-step comments to explain each instruction of the code. - The book is not just dealing with the background mathematics alone or only the programs but beautifully correlates the background mathematics to the theory and then finally translating it into the programs. - A rich set of chapter-end exercises are provided, consisting of both short-answer questions and long-answer questions. DESCRIPTION This book introduces the fundamental concepts of Data Science, which has proved to be a major game-changer in business solving problems.Ê Topics covered in the book include fundamentals of Data Science, data preprocessing, data plotting and visualization, statistical data analysis, machine learning for data analysis, time-series analysis, deep learning for Data Science, social media analytics, business analytics, and Big Data analytics. The content of the book describes the fundamentals of each of the Data Science related topics together with illustrative examples as to how various data analysis techniques can be implemented using different tools and libraries of Python programming language. Each chapter contains numerous examples and illustrative output to explain the important basic concepts. An appropriate number of questions is presented at the end of each chapter for self-assessing the conceptual understanding. The references presented at the end of every chapter will help the readers to explore more on a given topic.Ê WHAT WILL YOU LEARNÊ Perform processing on data for making it ready for visual plot and understand the pattern in data over time. Understand what machine learning is and how learning can be incorporated into a program. Know how tools can be used to perform analysis on big data using python and other standard tools. Perform social media analytics, business analytics, and data analytics on any data of a company or organization. WHO THIS BOOK IS FOR The book is for readers with basic programming and mathematical skills. The book is for any engineering graduates that wish to apply data science in their projects or wish to build a career in this direction. The book can be read by anyone who has an interest in data analysis and would like to explore more out of interest or to apply it to certain real-life problems. TABLE OF CONTENTS 1. Fundamentals of Data Science1 2. Data Preprocessing 3. Data Plotting and Visualization 4. Statistical Data Analysis 5. Machine Learning for Data Science 6. Time-Series Analysis 7. Deep Learning for Data Science 8. Social Media Analytics 9. Business Analytics 10. Big Data Analytics
Mongodb Fundamentals
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Author : Amit Phaltankar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-12-22
Mongodb Fundamentals written by Amit Phaltankar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-22 with Computers categories.
Learn how to deploy and monitor databases in the cloud, manipulate documents, visualize data, and build applications running on MongoDB using Node.js Key FeaturesLearn the fundamentals of NoSQL databases with MongoDBCreate, manage, and optimize a MongoDB database in the cloud using AtlasUse a real-world dataset to gain practical experience of handling big dataBook Description MongoDB is one of the most popular database technologies for handling large collections of data. This book will help MongoDB beginners develop the knowledge and skills to create databases and process data efficiently. Unlike other MongoDB books, MongoDB Fundamentals dives into cloud computing from the very start – showing you how to get started with Atlas in the first chapter. You will discover how to modify existing data, add new data into a database, and handle complex queries by creating aggregation pipelines. As you progress, you'll learn about the MongoDB replication architecture and configure a simple cluster. You will also get to grips with user authentication, as well as techniques for backing up and restoring data. Finally, you'll perform data visualization using MongoDB Charts. You will work on realistic projects that are presented as bitesize exercises and activities, allowing you to challenge yourself in an enjoyable and attainable way. Many of these mini-projects are based around a movie database case study, while the last chapter acts as a final project where you will use MongoDB to solve a real-world problem based on a bike-sharing app. By the end of this book, you'll have the skills and confidence to process large volumes of data and tackle your own projects using MongoDB. What you will learnSet up and use MongoDB Atlas on the cloudInsert, update, delete, and retrieve data from MongoDBBuild aggregation pipelines to perform complex queriesOptimize queries using indexesMonitor databases and manage user authorizationImprove scalability and performance with sharding clustersReplicate clusters, back up your database, and restore dataCreate data-driven charts and reports from real-time dataWho this book is for This book is designed for people who are new to MongoDB. It is suitable for developers, database administrators, system administrators, and cloud architects who are looking to use MongoDB for smooth data processing in the cloud. Although not necessary, basic knowledge of a general programming language and experience with other databases will help you grasp the topics covered more easily.
Kickstart Python Programming Fundamentals
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Author : Jit Sinha
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-06-24
Kickstart Python Programming Fundamentals written by Jit Sinha and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Computers categories.
TAGLINE Keep Calm and Let Us Tame the Python. KEY FEATURES ● Beginner-friendly with clear examples and no prior coding needed. ● Step-by-step projects from basics to real-world applications. ● Hands-on learning with flowcharts, functions, and data tools. DESCRIPTION Python is more than a programming language—it’s a career catalyst. Whether you're aiming to future-proof your skills, automate everyday tasks, or break into tech, Python is the gateway. Kickstart Python Programming Fundamentals is your launchpad, built specifically for absolute beginners, freshers, students, and professionals with no coding background. With crystal-clear explanations, real-world examples, and zero jargon, this book makes programming accessible, engaging, and fun. You’ll start by writing your first Python program and gradually master essential concepts like variables, loops, functions, and data structures. From there, you'll progress to object-oriented programming, file handling, working with databases, and even get a taste of AI and data analysis. Each chapter includes hands-on exercises and mini-projects to solidify your learning. By the end, you'll not only understand Python—you’ll be building real-world solutions, building a project portfolio, and ready to take on academic, personal, or professional challenges. The future is coded—start your journey today and don’t get left behind. WHAT WILL YOU LEARN ● Write and run your first Python programs with confidence. ● Understand and use variables, data types, and Python syntax. ● Build logic-driven programs using loops and conditionals. ● Create clean, reusable code with functions and parameters. ● Organize and manipulate data using lists, dictionaries, tuples, and sets. ● Read and write files, handle errors, and explore basic AI concepts. ● Apply your skills in real-world projects and coding challenges. WHO IS THIS BOOK FOR? This book is for absolute beginners, including students, fresh graduates, hobbyists, career switchers, and professionals from non-technical backgrounds. Whether you're a complete novice, a fresher with no coding experience, or simply curious about programming, this book offers a clear, hands-on path to start your journey with Python—no prior knowledge required. TABLE OF CONTENTS 1. Beginning with Python 2. Introduction to Algorithms and Flowcharts 3. Basic Python 4. Making Choices and Repeating Actions 5. Creating Functions 6. Organizing Data 7. Understanding OOP in Python 8. Using Modules and Packages 9. Error Handling 10. File Handling and String Manipulation 11. Dates and Times 12. Working with JSON and XML 13. Math in Python 14. Managing Packages with PIP 15. Building Web Apps 16. Python and Databases 17. Analyzing Data 18. Python in Artificial Intelligence 19. Conclusion and Next Steps 20. Real-World Project Index