100DaysofMLCode
My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
Install / Use
/learn @NishkarshRaj/100DaysofMLCodeAbout this skill
Quality Score
0/100
Category
Customer SupportSupported Platforms
Universal
Tags
100daysofcode100daysofmlcodeartificial-intelligenceartificial-neural-networksbig-dataclassificationclassification-algorithmdeep-learninggenerative-aihacktoberfestlinear-algebralinear-regressionllmmachine-learningneural-networkspolynomial-regressionpythonregressionregression-modelsscikitlearn-machine-learning
README
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Table of Contents
- Importing Libraries
- Importing Data sets
- Handling the missing data values
- Encoding categorical data
- Split Data into Train data and Test data
- Feature Scaling
- Simple Linear Regression
- Multi Linear Regression
- Polynomial Regression
- Support Vector Regression
- Decision Tree Regression
- Random Forest Regression
- Logistic Regression
- K Nearest Neighbors Classification
- Support Vector Machine
- Kernel SVM
- Naive Bayes
- Decision Tree Classification
- Random Forest Classification
7. Natural Language Processing
11. Data Visualization
- Matplotlib library in Python
- Tableau
- Power BI
- Grafana
Log of my Day-to-Day Activities
Track my daily activities here
How to Contribute
This is an open project and contribution in all forms are welcomed. Please follow these Contribution Guidelines
Code of Conduct
Adhere to the GitHub specified community code.
License
Check the official MIT License here.
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