ashishpatel26 / Amazing-Feature-EngineeringLinks
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
☆737Updated last month
Alternatives and similar repositories for Amazing-Feature-Engineering
Users that are interested in Amazing-Feature-Engineering are comparing it to the libraries listed below
Sorting:
- Python Feature Engineering Cookbook, published by Packt☆481Updated 2 years ago
- Code repository for the online course Feature Selection for Machine Learning☆324Updated 9 months ago
- Code repository for the online course Feature Engineering for Machine Learning☆395Updated last year
- A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning☆593Updated 6 years ago
- Data Science Feature Engineering and Selection Tutorials☆286Updated last month
- Complete-Life-Cycle-of-a-Data-Science-Project☆618Updated last year
- Code repository for the online course Machine Learning with Imbalanced Data☆180Updated 8 months ago
- Interpretable Machine Learning with Python, published by Packt☆468Updated 2 years ago
- Goal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).☆806Updated 5 years ago
- Applied Machine Learning Explainability Techniques, published by Packt☆247Updated last year
- This repository hosts code for my Time Series videos part of playlist here - https://www.youtube.com/playlist?list=PL3N9eeOlCrP5cK0QRQxeJ…☆264Updated 2 years ago
- Cracking the Data Science Interview☆357Updated 5 years ago
- Code repository for the online course Hyperparameter Optimization for Machine Learning☆125Updated 10 months ago
- ☆131Updated 3 years ago
- English translation of the sample code to "Data Analysis Techniques to Win Kaggle" book☆32Updated 4 years ago
- Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt☆211Updated 2 months ago
- Methods with examples for Feature Selection during Pre-processing in Machine Learning.☆365Updated 5 years ago
- A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.☆1,586Updated 2 years ago
- Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng☆368Updated 2 years ago
- This is a repository which contains all my work related Machine Learning, AI and Data Science. This includes my graduate projects, machin…☆271Updated 2 years ago
- Engineering MLOps, published by Packt☆187Updated 2 years ago
- A list of working examples of Data Science Use Cases and Applications by Industry☆63Updated 5 years ago
- Labs and Project from the course "How to Win a Data Science Competition: Learn from Top Kagglers"☆146Updated 5 years ago
- Official Repo for the Efficient Python for Data Scientists Book. You can buy the book from here:☆572Updated 6 months ago
- Practical guidance for time series analysis in Python☆313Updated this week
- Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)☆680Updated last year
- Source Code for 'Hands-on Time Series Analysis with Python' by B V Vishwas and Ashish Patel☆362Updated 4 years ago
- Customer Segmentation, RFM analysis and price elasticity☆19Updated 4 years ago
- A quick crash course in understanding the essentials of TensorFlow 2 and the integrated Keras API☆228Updated 4 years ago
- Machine Learning Experiments and Work☆651Updated 2 years ago