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Feature Engineering Bookcamp


Feature Engineering Bookcamp
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Feature Engineering Bookcamp


Feature Engineering Bookcamp
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Author : Sinan Ozdemir
language : en
Publisher: Simon and Schuster
Release Date : 2022-10-04

Feature Engineering Bookcamp written by Sinan Ozdemir 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 2022-10-04 with Computers categories.


Deliver huge improvements to your machine learning pipelines without spending hours fine-tuning parameters! This book’s practical case studies reveal feature engineering techniques that upgrade your data wrangling—and your ML results. Feature Engineering Bookcamp guides you through a collection of projects that give you hands-on practice with core feature engineering techniques. You’ll work with feature engineering practices that speed up the time it takes to process data and deliver real improvements in your model’s performance. This instantly-useful book skips the abstract mathematical theory and minutely-detailed formulas; instead you’ll learn through interesting code-driven case studies, including tweet classification, COVID detection, recidivism prediction, stock price movement detection, and more.



Feature Engineering For Machine Learning


Feature Engineering For Machine Learning
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Author : Alice Zheng
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-03-23

Feature Engineering For Machine Learning written by Alice Zheng 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 2018-03-23 with Computers categories.


Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering. Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples. You’ll examine: Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms Natural text techniques: bag-of-words, n-grams, and phrase detection Frequency-based filtering and feature scaling for eliminating uninformative features Encoding techniques of categorical variables, including feature hashing and bin-counting Model-based feature engineering with principal component analysis The concept of model stacking, using k-means as a featurization technique Image feature extraction with manual and deep-learning techniques



The Art Of Feature Engineering


The Art Of Feature Engineering
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Author : Pablo Duboue
language : en
Publisher: Cambridge University Press
Release Date : 2020-06-25

The Art Of Feature Engineering written by Pablo Duboue and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-25 with Computers categories.


A practical guide for data scientists who want to improve the performance of any machine learning solution with feature engineering.



Machine Learning Bookcamp


Machine Learning Bookcamp
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Author : Alexey Grigorev
language : en
Publisher: Simon and Schuster
Release Date : 2021-11-23

Machine Learning Bookcamp written by Alexey Grigorev 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 2021-11-23 with Computers categories.


Time to flex your machine learning muscles! Take on the carefully designed challenges of the Machine Learning Bookcamp and master essential ML techniques through practical application. Summary In Machine Learning Bookcamp you will: Collect and clean data for training models Use popular Python tools, including NumPy, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images Deploy ML models to a production-ready environment The only way to learn is to practice! In Machine Learning Bookcamp, you’ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image analysis, each new project builds on what you’ve learned in previous chapters. You’ll build a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Master key machine learning concepts as you build actual projects! Machine learning is what you need for analyzing customer behavior, predicting price trends, evaluating risk, and much more. To master ML, you need great examples, clear explanations, and lots of practice. This book delivers all three! About the book Machine Learning Bookcamp presents realistic, practical machine learning scenarios, along with crystal-clear coverage of key concepts. In it, you’ll complete engaging projects, such as creating a car price predictor using linear regression and deploying a churn prediction service. You’ll go beyond the algorithms and explore important techniques like deploying ML applications on serverless systems and serving models with Kubernetes and Kubeflow. Dig in, get your hands dirty, and have fun building your ML skills! What's inside Collect and clean data for training models Use popular Python tools, including NumPy, Scikit-Learn, and TensorFlow Deploy ML models to a production-ready environment About the reader Python programming skills assumed. No previous machine learning knowledge is required. About the author Alexey Grigorev is a principal data scientist at OLX Group. He runs DataTalks.Club, a community of people who love data. Table of Contents 1 Introduction to machine learning 2 Machine learning for regression 3 Machine learning for classification 4 Evaluation metrics for classification 5 Deploying machine learning models 6 Decision trees and ensemble learning 7 Neural networks and deep learning 8 Serverless deep learning 9 Serving models with Kubernetes and Kubeflow



Data Science Bookcamp


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



Powerful Python


Powerful Python
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Author : Aaron Maxwell
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-11-08

Powerful Python written by Aaron Maxwell 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 2024-11-08 with categories.


Once you've mastered the basics of Python, how do you skill up to the top 1%? How do you focus your learning time on topics that yield the most benefit for production engineering and data teams—without getting distracted by info of little real-world use? This book answers these questions and more. Based on author Aaron Maxwell's software engineering career in Silicon Valley, this unique book focuses on the Python first principles that act to accelerate everything else: the 5% of programming knowledge that makes the remaining 95% fall like dominos. It's also this knowledge that helps you become an exceptional Python programmer, fast. Learn how to think like a Pythonista: explore advanced Pythonic thinking Create lists, dicts, and other data structures using a high-level, readable, and maintainable syntax Explore higher-order function abstractions that form the basis of Python libraries Examine Python's metaprogramming tool for priceless patterns of code reuse Master Python's error model and learn how to leverage it in your own code Learn the more potent and advanced tools of Python's object system Take a deep dive into Python's automated testing and TDD Learn how Python logging helps you troubleshoot and debug more quickly



Engineering Of Additive Manufacturing Features For Data Driven Solutions


Engineering Of Additive Manufacturing Features For Data Driven Solutions
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Author : Mutahar Safdar
language : en
Publisher: Springer Nature
Release Date : 2023-06-01

Engineering Of Additive Manufacturing Features For Data Driven Solutions written by Mutahar Safdar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-01 with Technology & Engineering categories.


This book is a comprehensive guide to the latest developments in data-driven additive manufacturing (AM). From data mining and pre-processing to signal processing, computer vision, and more, the book covers all the essential techniques for preparing AM data. Readers willl explore the key physical and synthetic sources of AM data throughout the life cycle of the process and learn about feature engineering techniques, pipelines, and resulting features, as well as their applications at each life cycle phase. With a focus on featurization efforts from reviewed literature, this book offers tabular summaries for major data sources and analyzes feature spaces at the design, process, and structure phases of AM to uncover trends and insights specific to feature engineering techniques. Finally, the book discusses current challenges and future directions, including AI/ML/DL readiness of AM data. Whether you're an expert or newcomer to the field, this book provides a broader summary of the status and future of data-driven AM technology.



Rewired


Rewired
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Author : Eric Lamarre
language : en
Publisher: John Wiley & Sons
Release Date : 2023-06-13

Rewired written by Eric Lamarre 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 2023-06-13 with Business & Economics categories.


In Rewired, the world's most influential management consulting firm, McKinsey & Company, delivers a road-tested, how-to manual their own consultants use to help companies build the capabilities to outcompete in the age of digital and AI. Many companies are stuck with digital transformations that are not moving the needle. There are no quick fixes but there is a playbook. The answer is in rewiring your business so hundreds, thousands, of teams can harness technology to continuously create great customer experiences, lower unit costs, and generate value. It's the capabilities of the organization that win the race. McKinsey Digital's top leaders Eric Lamarre, Kate Smaje and Rodney W. Zemmel provide proven how-to details on what it takes in six comprehensive sections – creating the transformation roadmap, building a talent bench, adopting a new operating model, producing a distributed technology environment so teams can innovate, embedding data everywhere, and unlocking user adoption and enterprise scaling. Tested, iterated, reworked, and tested again over the years, McKinsey's digital and AI transformation playbook is captured in the pages of Rewired. It contains diagnostic assessments, operating model designs, technology and data architecture diagrams, how-to checklists, best practices and detailed implementation methods, all exemplified with demonstrated case studies and illustrated with 100+ exhibits. Rewired is for leaders who are ready to roll up their sleeves and do the hard work needed to rewire their company for long-term success.



Bug Bounty Bootcamp


Bug Bounty Bootcamp
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Author : Vickie Li
language : en
Publisher: No Starch Press
Release Date : 2021-11-16

Bug Bounty Bootcamp written by Vickie Li and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-16 with Computers categories.


Bug Bounty Bootcamp teaches you how to hack web applications. You will learn how to perform reconnaissance on a target, how to identify vulnerabilities, and how to exploit them. You’ll also learn how to navigate bug bounty programs set up by companies to reward security professionals for finding bugs in their web applications. Bug bounty programs are company-sponsored programs that invite researchers to search for vulnerabilities on their applications and reward them for their findings. This book is designed to help beginners with little to no security experience learn web hacking, find bugs, and stay competitive in this booming and lucrative industry. You’ll start by learning how to choose a program, write quality bug reports, and maintain professional relationships in the industry. Then you’ll learn how to set up a web hacking lab and use a proxy to capture traffic. In Part 3 of the book, you’ll explore the mechanisms of common web vulnerabilities, like XSS, SQL injection, and template injection, and receive detailed advice on how to find them and bypass common protections. You’ll also learn how to chain multiple bugs to maximize the impact of your vulnerabilities. Finally, the book touches on advanced techniques rarely covered in introductory hacking books but that are crucial to understand to hack web applications. You’ll learn how to hack mobile apps, review an application’s source code for security issues, find vulnerabilities in APIs, and automate your hacking process. By the end of the book, you’ll have learned the tools and techniques necessary to be a competent web hacker and find bugs on a bug bounty program.



Devops Bootcamp


Devops Bootcamp
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Author : Mitesh Soni
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-05-30

Devops Bootcamp written by Mitesh Soni 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 2017-05-30 with Computers categories.


Sharpen your DevOps knowledge with DevOps Bootcamp About This Book Improve your organization's performance to ensure smooth production of software and services. Learn how Continuous Integration and Continuous Delivery practices can be utilized to cultivate the DevOps culture. A fast-paced guide filled with illustrations and best practices to help you consistently ship quality software. Who This Book Is For The book is aimed at IT Developers and Operations—administrators who want to quickly learn and implement the DevOps culture in their organization. What You Will Learn Static Code Analysis using SOnarqube Configure a Maven-based JEE Web Application Perform Continuous Integration using Jenkins and VSTS Install and configure Docker Converge a Chef node using a Chef workstation Accomplish Continuous Delivery in Microsoft Azure VM and Microsoft Azure App Services (Azure Web Apps) using Jenkins Perform Load Testing using Apache JMeter Build and Release Automation using Visual Studio Team Services Monitor Cloud-based resources In Detail DevOps Bootcamp delivers practical learning modules in manageable chunks. Each chunk is delivered in a day, and each day is a productive one. Each day builds your competency in DevOps. You will be able to take the task you learn every day and apply it to cultivate the DevOps culture. Each chapter presents core concepts and key takeaways about a topic in DevOps and provides a series of hands-on exercises. You will not only learn the importance of basic concepts or practices of DevOps but also how to use different tools to automate application lifecycle management. We will start off by building the foundation of the DevOps concepts. On day two, we will perform Continuous Integration using Jenkins and VSTS both by configuring Maven-based JEE Web Application?. We will also integrate Jenkins and Sonar qube for Static Code Analysis. Further, on day three, we will focus on Docker containers where we will install and configure Docker and also create a Tomcat Container to deploy our Java based web application. On day four, we will create and configure the environment for application deployment in AWS and Microsoft Azure Cloud for which we will use Infrastructure as a Service and Open Source Configuration Management tool Chef. For day five, our focus would be on Continuous Delivery. We will automate application deployment in Docker container using Jenkins Plugin, AWS EC2 using Script, AWS Elastic Beanstalk using Jenkins Plugin, Microsoft Azure VM using script, and Microsoft Azure App Services Using Jenkins. We will also configure Continuous Delivery using VSTS. We will then learn the concept of Automated Testing on day six using Apache JMeter and URL-based tests in VSTS. Further, on day seven, we will explore various ways to automate application lifecycle management using orchestration. We will see how Pipeline can be created in Jenkins and VSTS, so the moment Continuous? Integration is completed successfully, Continuous Delivery will start and application will be deployed. On the final day, our focus would be on Security access to Jenkins and Monitoring of CI resources, and cloud-based resources in AWS and Microsoft Azure Platform as a Service. Style and Approach This book is all about fast and intensive learning. This means we don't waste time in helping readers get started. The new content is basically about filling in with highly-effective examples to build new things, solving problems in newer and unseen ways, and solving real-world examples.