Master Python Data Engineering With Virtual Ai Tutoring
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Master Python Data Engineering With Virtual Ai Tutoring
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Author : Diego Rodrigues
language : en
Publisher: Diego Rodrigues
Release Date : 2024-11-19
Master Python Data Engineering With Virtual Ai Tutoring written by Diego Rodrigues and has been published by Diego Rodrigues this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-19 with Business & Economics categories.
Imagine acquiring a book and, as a bonus, gaining access to a 24/7 AI-assisted Virtual Tutoring to personalize your learning journey, reinforce knowledge, and receive mentorship for developing and implementing real projects... ...Welcome to the Revolution of Personalized Learning with AI-Assisted Virtual Tutoring! Discover " MASTER PYTHON DATA ENGINEERING: From Fundamentals to Advanced Applications with Virtual AI Tutoring," the essential guide for professionals and enthusiasts who want to master data engineering with Python. This innovative manual, written by Diego Rodrigues, an author with over 140 titles published in six languages, combines high-quality content with the advanced technology of IAGO, a virtual tutor developed and hosted on the OpenAI platform. Innovative Features: Personalized Learning: IAGO adapts the content to your knowledge level, offering detailed explanations and personalized exercises. Immediate Feedback: Receive corrections and suggestions in real time, speeding up your learning process. Interactivity and Engagement: Interact with the tutor via text or voice, making learning more dynamic and motivating. Project Development Mentorship: Get practical guidance to develop and implement real projects, applying the knowledge gained. Total Flexibility: Access the tutor anywhere, anytime, whether on a desktop, notebook, or smartphone with web access. Take advantage of the Limited-Time Launch Promotional Price! Don't miss the opportunity to transform your learning journey with an innovative and effective method. This book has been carefully structured to meet your needs and exceed your expectations, ensuring you are prepared to face challenges and seize opportunities in the field of data engineering. Open the book sample and discover how to access the select club of cutting-edge technology professionals. Take advantage of this unique opportunity and achieve your goals! TAGS: data engineering automation science big Pandas NumPy Dask SQLAlchemy web scraping BeautifulSoup Scrapy APIs ETL DataOps Data Lakes Data Warehouses AWS Google Cloud Microsoft Azure Hadoop Spark machine learning artificial intelligence data pipelines data visualization Matplotlib Seaborn data analysis relational databases NoSQL MongoDB Apache Airflow Kafka real-time data governance data security compliance mentorship Diego Rodrigues Tableau Power BI Snowflake Informatica Alation Talend Apache Flink Jupyter Notebooks DevOps Databricks Cloudera Hortonworks Teradata IBM Cloud Oracle Cloud Salesforce SAP HANA ElasticSearch Redis Kubernetes Docker Jenkins GitHub GitLab Continuous Integration Continuous Deployment CI/CD digital transformation predictive analysis business intelligence IoT Internet of Things smart cities connected health Industry 4.0 fintechs retail education marketing competitive intelligence data science automated testing custom reports operational efficiency Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes Kali Linux Nmap Metasploit Wireshark information security pen test cybersecurity Linux distributions ethical hacking vulnerability analysis system exploration wireless attacks web application security malware analysis social engineering Android iOS Social Engineering Toolkit SET computer science IT professionals cybersecurity careers cybersecurity expertise cybersecurity library cybersecurity training Linux operating systems cybersecurity tools ethical hacking tools security testing penetration test cycle security concepts mobile security cybersecurity fundamentals cybersecurity techniques skills cybersecurity industry global cybersecurity trends Kali Linux tools education innovation penetration test tools best practices global companies cybersecurity solutions IBM Google Microsoft AWS Cisco Oracle consulting cybersecurity framework network security courses cybersecurity tutorials Linux security challenges landscape cloud security threats compliance research technology React Native Flutter Ionic Xamarin HTML CSS JavaScript Java Kotlin Swift Objective-C Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Angular Vue.js Bitrise GitHub Actions Material Design Cupertino Fastlane Appium Selenium Jest CodePush Firebase Expo Visual Studio C# .NET Azure Google Play App Store CodePush IoT AR VR
Master Python Data Science Wiith Ai Virtual Tutoring
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Author : Diego Rodrigues
language : en
Publisher: Diego Rodrigues
Release Date : 2024-11-19
Master Python Data Science Wiith Ai Virtual Tutoring written by Diego Rodrigues and has been published by Diego Rodrigues this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-19 with Business & Economics categories.
Imagine acquiring a complete book and, as a bonus, receiving access to a 24/7 AI-assisted Virtual Tutoring to personalize your learning journey, knowledge consolidation, and mentorship for the development and implementation of real projects... ... Welcome to the Revolution of Personalized Learning with AI-Assisted Virtual Tutoring! Discover "MASTER PYTHON: DATA SCIENCE From Fundamentals to Advanced Applications with AI Virtual Tutoring" the essential guide for professionals and enthusiasts who wish to master data science with Python. This innovative manual, written by Diego Rodrigues, an author with over 140 titles published in six languages, combines high-quality content with the advanced technology of IAGO, a virtual tutor developed and hosted on the OpenAI platform. The book begins with a comprehensive introduction to data science, highlighting the importance of the field and the crucial role Python plays. Next, it covers the fundamentals of Python, including basic syntax, data structures, and control flow, laying a solid foundation for subsequent chapters. You will learn essential data manipulation and cleaning techniques using libraries like Pandas and NumPy, ensuring your data is ready for analysis. Then, you will explore exploratory data analysis (EDA) with tools like Matplotlib and Seaborn to discover valuable patterns and insights. Data visualization is deepened with the use of Plotly to create interactive charts and Dash to develop dynamic dashboards. The book progresses to machine learning, introducing basic concepts and types of learning, followed by data preparation and model implementation with Scikit-Learn. Linear and polynomial regression techniques are explained in detail, along with model performance evaluation. You will also delve into advanced machine learning with chapters on classification, clustering, and dimensionality reduction. Natural language processing (NLP) techniques are covered, using libraries like NLTK and SpaCy. The deep learning section covers everything from basic neural networks to advanced applications with TensorFlow and Keras, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The book also explores big data, teaching how to work with large volumes of data using Hadoop and Spark with Python. It concludes with a comprehensive guide on conducting a data science project from start to finish and discusses ethics and responsibility in data science, addressing best practices and regulations. Take advantage of the Limited Time Launch Promotional Price! Open the book sample and discover how to join the select club of cutting-edge technology professionals. Take this unique opportunity and achieve your goals! TAGS data science manipulation data analysis visualization Pandas NumPy Matplotlib Seaborn Plotly Dash machine learning deep learning Scikit-Learn TensorFlow Keras big data Hadoop Spark exploratory analysis EDA models regression classification clustering NLP natural language processing convolutional neural networks CNNs recurrent RNNs supervised learning unsupervised learning reinforcement learning digital transformation predictive analysis artificial intelligence Diego Rodrigues applied data science real projects virtual tutoring OpenAI IAGO task automation modeling prediction advanced techniques SQL time series analysis social network analysis interactive data visualization data storytelling Python programming data science ethics data privacy regulations cybersecurity data collection data processing data engineering statistical analysis real-time visualization automated reports data-driven aws google ibm meta azure Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes Kali Linux Nmap Metasploit Wireshark information security pen test cybersecurity Linux distributions ethical hacking vulnerability analysis system exploration wireless attacks web application security malware analysis social engineering Android iOS Social Engineering Toolkit SET computer science IT professionals cybersecurity careers cybersecurity expertise cybersecurity library cybersecurity training Linux operating systems cybersecurity tools ethical hacking tools security testing penetration test cycle security concepts mobile security cybersecurity fundamentals cybersecurity techniques skills cybersecurity industry global cybersecurity trends Kali Linux tools education innovation penetration test tools best practices global companies cybersecurity solutions IBM Google Microsoft AWS Cisco Oracle consulting cybersecurity framework network security courses cybersecurity tutorials Linux security challenges landscape cloud security threats compliance research technology React Native Flutter Ionic Xamarin HTML CSS JavaScript Java Kotlin Swift Objective-C Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Angular Vue.js Bitrise GitHub Actions Material Design Cupertino Fastlane Appium Selenium Jest CodePush Firebase Expo Visual Studio C# .NET Azure Google Play App Store CodePush IoT AR VR
Master Python Cybersecurity With Ai Virtual Tutoring
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Author : Diego Rodrigues
language : en
Publisher: Diego Rodrigues
Release Date : 2024-11-19
Master Python Cybersecurity With Ai Virtual Tutoring written by Diego Rodrigues and has been published by Diego Rodrigues this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-19 with Business & Economics categories.
Imagine acquiring a book and, as a bonus, getting access to a 24/7 AI-assisted Virtual Tutoring to personalize your learning journey, consolidate knowledge, and receive mentorship for developing and implementing real projects... ... Welcome to the Revolution of Personalized Learning with AI-Assisted Virtual Tutoring! Discover "MASTER PYTHON CYBERSECURITY: From Fundamentals to Advanced Applications with AI Virtual Tutoring," the essential guide for professionals and enthusiasts aiming to master automation and cybersecurity with Python. This innovative manual, written by Diego Rodrigues, a renowned author with over 140 titles published in six languages, combines high-quality content with advanced technology from IAGO, a virtual tutor developed and hosted on the OpenAI platform. Innovative Features: - Personalized Learning: IAGO adapts the content according to your knowledge level, offering detailed explanations and personalized exercises. - Immediate Feedback: Receive corrections and suggestions in real-time, accelerating your learning process. - Interactivity and Engagement: Interact with the tutor via text or voice, making the study more dynamic and motivating. - Mentorship for Project Development: Get practical guidance to develop and implement real projects, applying the knowledge acquired. - Total Flexibility: Access the tutor anywhere and anytime, whether on desktop, notebook, or smartphone with web access. Take Advantage of the Limited Time Launch Promotional Price! Don't miss the opportunity to transform your learning journey with an innovative and effective method. This book has been carefully structured to meet your needs and exceed your expectations, ensuring you are prepared to face challenges and seize opportunities in the field of automation and cybersecurity. Open the book sample and discover how to join the select club of cutting-edge technology professionals. Take advantage of this unique opportunity and achieve your goals! TAGS hacking automation cybersecurity Scapy Requests BeautifulSoup Nmap Metasploit ethical hacking penetration testing forensic analysis vulnerabilities network security encryption cyber attacks data protection network monitoring security audit advanced techniques cyber defense information security system security invasion protection Diego Rodrigues CyberExtreme malware virus phishing DDoS attacks artificial intelligence machine learning blockchain DevOps DevSecOps SCADA security industry 4.0 connected health smart cities vulnerability analysis web application security SQL Injection XSS CSRF patch management software update password policy multi-factor authentication MFA encryption AES RSA ECC cloud security AWS Microsoft Azure Google Cloud IBM Cloud Palo Alto Networks Cisco Systems Check Point Symantec McAfee Splunk CrowdStrike Fortinet Tenable Nessus OpenVAS Wi-Fi security LTE 5G endpoints APIs osint encryption at rest risk-based risk management log analysis continuous monitoring threat response behavior analysis security tools best practices innovation digital transformation big data hack Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes Kali Linux Nmap Metasploit Wireshark information security pen test cybersecurity Linux distributions ethical hacking vulnerability analysis system exploration wireless attacks web application security malware analysis social engineering Android iOS Social Engineering Toolkit SET computer science IT professionals cybersecurity careers cybersecurity expertise cybersecurity library cybersecurity training Linux operating systems cybersecurity tools ethical hacking tools security testing penetration test cycle security concepts mobile security cybersecurity fundamentals cybersecurity techniques skills cybersecurity industry global cybersecurity trends Kali Linux tools education innovation penetration test tools best practices global companies cybersecurity solutions IBM Google Microsoft AWS Cisco Oracle consulting cybersecurity framework network security courses cybersecurity tutorials Linux security challenges landscape cloud security threats compliance research technology React Native Flutter Ionic Xamarin HTML CSS JavaScript Java Kotlin Swift Objective-C Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Angular Vue.js Bitrise GitHub Actions Material Design Cupertino Fastlane Appium Selenium Jest CodePush Firebase Expo Visual Studio C# .NET Azure Google Play App Store CodePush IoT AR VR GITHUB
Artificial Intelligence With Python
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Author : Prateek Joshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-01-27
Artificial Intelligence With Python written by Prateek Joshi 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 2017-01-27 with Computers categories.
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
Deep Learning For Coders With Fastai And Pytorch
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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29
Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Ai Tutors The Future Of Personalized Education
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Author : Ahmed Musa
language : en
Publisher: Recorded Books
Release Date : 2024-12-26
Ai Tutors The Future Of Personalized Education written by Ahmed Musa and has been published by Recorded Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-26 with Technology & Engineering categories.
Artificial intelligence has the potential to revolutionize education by offering personalized learning experiences tailored to individual students' needs. This book examines how AI tutors are transforming classrooms, providing real-time feedback, adaptive learning paths, and targeted support. Learn how AI-powered platforms are helping students master subjects at their own pace while providing teachers with valuable insights into student performance. With predictions for the future of AI in education, this book is an essential guide to understanding the role of artificial intelligence in personalized learning.
Exploring The Advancements And Future Directions Of Digital Twins In Healthcare 6 0
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Author : Dubey, Archi
language : en
Publisher: IGI Global
Release Date : 2024-07-18
Exploring The Advancements And Future Directions Of Digital Twins In Healthcare 6 0 written by Dubey, Archi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-18 with Computers categories.
The healthcare industry is increasingly complex, demanding personalized treatments and efficient operational processes. Traditional research methods need help to keep pace with these demands, often leading to inefficiencies and suboptimal outcomes. Integrating digital twin technology presents a promising solution to these challenges, offering a virtual platform for modeling and simulating complex healthcare scenarios. However, the full potential of digital twins still needs to be explored mainly due to a lack of comprehensive guidance and practical insights for researchers and practitioners. Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0 is not just a theoretical exploration. It is a practical guide that bridges the gap between theory and practice, offering real-world case studies, best practices, and insights into personalized medicine, real-time patient monitoring, and healthcare process optimization. By equipping you with the knowledge and tools needed to effectively integrate digital twins into your healthcare research and operations, this book is a valuable resource for researchers, academicians, medical practitioners, scientists, and students.
Pandas In 7 Days
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Author : Fabio Nelli
language : en
Publisher: BPB Publications
Release Date : 2022-04-25
Pandas In 7 Days written by Fabio Nelli and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-25 with Computers categories.
Make data analysis fast, reliable, and clean with Python, Pandas and Matplotlib. KEY FEATURES ● A detailed walk-through of the Pandas library's features with multiple examples. ● Numerous graphical representations and reporting capabilities using popular Matplotlib. ● A high-level overview of extracting data from including files, databases, and the web. DESCRIPTION No matter how large or small your dataset is, the author 'Fabio Nelli' simply used this book to teach all the finest technical coaching on applying Pandas to conduct data analysis with zero worries. Both newcomers and seasoned professionals will benefit from this book. It teaches you how to use the pandas library in just one week. Every day of the week, you'll learn and practise the features and data analysis exercises listed below: Day 01: Get familiar with the fundamental data structures of pandas, including Declaration, data upload, indexing, and so on. Day 02: Execute commands and operations related to data selection and extraction, including slicing, sorting, masking, iteration, and query execution. Day 03: Advanced commands and operations such as grouping, multi-indexing, reshaping, cross-tabulations, and aggregations. Day 04: Working with several data frames, including comparison, joins, concatenation, and merges. Day 05: Cleaning, pre-processing, and numerous strategies for data extraction from external files, the web, databases, and other data sources. Day 06: Working with missing data, interpolation, duplicate labels, boolean data types, text data, and time-series datasets. Day 07: Introduction to Jupyter Notebooks, interactive data analysis, and analytical reporting with Matplotlib's stunning graphics. WHAT YOU WILL LEARN ●Extract, cleanse, and process data from databases, text files, HTML pages, and JSON data. ●Work with DataFrames and Series, and apply functions to scale data manipulations. ●Graph your findings using charts typically used in modern business analytics. ●Learn to use all of the pandas basic and advanced features independently. ● Storing and manipulating labeled/columnar data efficiently. WHO THIS BOOK IS FOR If you're looking to expedite a data science or sophisticated data analysis project, you've come to the perfect place. Each data analysis topic is covered step-by-step with real-world examples. Python knowledge isn't required however, knowing a little bit helps. TABLE OF CONTENTS 1. Pandas, the Python library 2. Setting up a Data Analysis Environment 3. Day 1 - Data Structures in Pandas library 4. Day 2 - Working within a DataFrame, Basic Functionalities 5. Day 3 - Working within a DataFrame, Advanced Functionalities 6. Day 4 - Working with two or more DataFrames 7. Day 5 - Working with data sources and real-word datasets 8. Day 6 - Troubleshooting Challenges wit Real Datasets 9. Day 7 - Data Visualization and Reporting 10. Conclusion – Moving Beyond
Mathematics For Machine Learning
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Author : Marc Peter Deisenroth
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-23
Mathematics For Machine Learning written by Marc Peter Deisenroth 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 2020-04-23 with Computers categories.
Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.
Understanding Machine Learning
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Author : Shai Shalev-Shwartz
language : en
Publisher: Cambridge University Press
Release Date : 2014-05-19
Understanding Machine Learning written by Shai Shalev-Shwartz 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 2014-05-19 with Computers categories.
Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.