Published 7/2024
Created by Henrik Johansson
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 68 Lectures ( 28h 30m ) | Size: 11 GB
Learn to Master Classification with Pandas and Python for Data Science and Machine Learning[2024]
What you’ll learn:
Master Classification both in theory and practice
Master Classification models from Logistic Regression to the Gaussian Naïve Bayes Classifier model
Use practical classification hands-on theory and learn to execute advanced Classification tasks with ease
Use advanced Decision Tree, Random Forest, and Voting Classifier models
Use Feedforward Multilayer Networks and Advanced Classifier model Structures
Use effective decision surfaces graphs and other tools to judge Classifier performance
Use the Scikit-learn library for Classification supported by Matplotlib, Seaborn, Pandas, and Python
Master Python 3 programming with Python’s native data structures, data transformers, functions, object orientation, and logic
Use and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File Handling
Use Python’s advanced object-oriented programming and make your own custom objects, functions and how to generalize functions
Manipulate data and use advanced multi-dimensional uneven data structures
Master the Pandas 2 and 3 library for Advanced Data Handling
Use the language and fundamental concepts of the Pandas library and to handle all aspects of creating, changing, and selecting Data from a Pandas DataFrame
Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods
Perform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of data
Make advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group data
Make advanced Data Visualizations with Pandas, Matplotlib, and Seaborn
Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
Requirements:
Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
Access to a computer with an internet connection
Programming experience is not needed and you will be taught everything you need
The course only uses costless software
Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included
Description:
Welcome to the course Master Classification with Pandas and Python!This three-in-one master class video course will teach you to master Classification, Python 3, Pandas 2 + 3, and advanced Data Handling.You will learn to master Classification with a number of advanced Classification techniques. You will learn to handle advanced model structures such as feedforward artificial neural networks for classification tasks.Python 3 is one of the most popular and useful programming languages in the world, and Pandas 2 and future version 3 is the most powerful, efficient, and useful Data Handling library in existence.You will learn to master Python’s native building blocks and powerful object-oriented programming. You will design your own advanced constructions of Python’s building blocks and execute detailed Data Handling tasks with Python.You will learn to master the Pandas library and to use its powerful Data Handling techniques for advanced Data Science and Machine Learning Data Handling tasks. The Pandas library is a fast, powerful, flexible, and easy-to-use open-source data analysis and data manipulation tool, which is directly usable with the Python programming language.You will learn to:Master Classification both in theory and practiceMaster Classification models from Logistic Regression to the Gaussian Naïve Bayes Classifier modelUse practical classification hands-on theory and learn to execute advanced Classification tasks with easeUse advanced Decision Tree, Random Forest, and Voting Classifier modelsUse Feedforward Multilayer Networks and Advanced Classifier model StructuresUse effective decision surfaces and other tools to judge Classifier performanceUse the Scikit-learn library for Classification supported by Matplotlib, Seaborn, Pandas, and PythonMaster Python 3 programming with Python’s native data structures, data transformers, functions, object orientation, and logicUse and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File HandlingUse Python’s advanced object-oriented programming and make your own custom objects, functions and how to generalize functionsManipulate data and use advanced multi-dimensional uneven data structuresMaster the Pandas 2 and 3 library for Advanced Data HandlingUse the language and fundamental concepts of the Pandas library and to handle all aspects of creating, changing, modifying, and selecting Data from a Pandas DataFrame objectUse file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methodsPerform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of dataMake advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group dataMake advanced Data Visualizations with Pandas, Matplotlib, and SeabornCloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources.Option: To use the Anaconda Distribution (for Windows, Mac, Linux)Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work life.And much more…This course is an excellent way to learn to master Classification, Python, Pandas and Data Handling!Classification and Supervised Learning are one of the most important and common tasks Data Science, Machine Learning, modeling, and AI. Data Handling is the process of making data useful and usable for inter alia classification and data analysis.Most Data Scientists and Machine Learning Engineers spends about 80% of their working efforts and time on Data Handling tasks. Being good at Python, Pandas, and Data Handling are extremely useful and time-saving skills that functions as a force multiplier for productivity.This course is designed for everyone who wants tolearn to master Classificationlearn to Master Python 3 from scratch or the beginner levellearn to Master Python 3 and knows another programming languagereach the Master – intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learninglearn to Master the Pandas librarylearn Data Handling skills that work as a force multiplier and that they will have use of in their entire careerlearn advanced Data Handling and improve their capabilities and productivityRequirements:Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommendedAccess to a computer with an internet connectionProgramming experience is not needed and you will be taught everything you needThe course only uses costless softwareWalk-you-through installation and setup videos for Cloud computing and Windows 10/11 is includedThis course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Classification, Python, Pandas, and Data Handling.Enroll now to receive 25+ hours of video tutorials with manually edited English captions, and a certificate of completion after completing the course!
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