https://github.com/ankitmishralive/machinelearning
Continuously deep diving in understanding & advancing my expertise in Machine Learning through ongoing education and hands on experience with practical learning.
https://github.com/ankitmishralive/machinelearning
artificial-intelligence data-analysis data-cleaning data-gathering machine-learning machinel-learning-algorithms matplotlib numpy pandas python seaborn
Last synced: 11 months ago
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Continuously deep diving in understanding & advancing my expertise in Machine Learning through ongoing education and hands on experience with practical learning.
- Host: GitHub
- URL: https://github.com/ankitmishralive/machinelearning
- Owner: ankitmishralive
- Created: 2023-02-04T21:35:25.000Z (about 3 years ago)
- Default Branch: master
- Last Pushed: 2023-12-13T22:59:10.000Z (about 2 years ago)
- Last Synced: 2025-02-03T02:01:48.030Z (about 1 year ago)
- Topics: artificial-intelligence, data-analysis, data-cleaning, data-gathering, machine-learning, machinel-learning-algorithms, matplotlib, numpy, pandas, python, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 103 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Machine Learning and Ensemble Techniques Repository
## Overview
Welcome to the Machine Learning and Ensemble Techniques repository! This project encompasses a diverse set of modules focusing on various aspects of machine learning, ensemble techniques, and related topics this repository has something for you.
This repository not only covers the technical aspects of machine learning and ensemble techniques but also includes notes on important topics in both English and Hinglish.
Feel free to explore and contribute to the content. As time permits, more sets of content will be added, enhancing the repository's value as a learning and reference hub.
## Table of Contents
- [API Consumption/webapp](#api-consumptionwebapp)
- [API Dev](#api-dev)
- [Content Based Recommendation Engine](#content-based-recommendation-engine)
- [DAP](#dap)
- [Data Visualization](#data-visualization)
- [ETL using Amazon RDS ( Remaining )](#etl-using-amazon-rds--remaining-)
- [Ensemble Learning](#ensemble-learning)
- [ML Algos](#ml-algos-self-learning)
- [Numpy](#numpy)
- [Pandas](#pandas)
## DAP
It covers practical aspect of Data Analysis Process with some classical & interesting dataset.
## Data Visualization
Hands on Data Visualization using various libraries like matplotlib,seaborn & plotly.
## Content Based Recommendation Engine
## ETL using Amazon RDS ( Remaining )
Extract Transform Reload ! Remaining
## Ensemble Learning
All About Ensemble Techniques
## ML Algos
Covers all the Famous ML Algorithms
## Numpy
Hands on Numpy Attributes & its various function
## Pandas
Hands on Pandas Attributes & its various function