/30-days-of-Mahcine-Learning

This is me, trying to master Machine Learning concepts in 30 Days!! and I belive it is possible.

Primary LanguageJupyter Notebook

30-days-of-Machin[[handle_missing_data]]e-Learning

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DAY-01

  • Prediction of AirBnB's Sotck Price Value Using Decision Tree Regressor and Random Forest Regressor Algorithm link
  • Dataset link
  • Share

DAY-02

  • Basics for Machine Learning : Random number, Bootstraping, Correlation, Covarience, Data Distribution

DAY-03

  • Started new Stock dataset BTC price evaluation
  • The pandas of kaggle is running with the matplotlib all from its creator

DAY-04

  • Learn the matplotlib.pyplot from creator documents

DAY-05

  • Learn the seaborn, ann, svr and work on the BTC price data
  • Bitcoin prediction: dataset : [link]
  • collab link: link

DAY-06

DAY-07

  • Completed the Seaborn sample project.
  • Google Colab Link: [link]

DAY-08

DAY-09

DAY-10

  • learn EDA with covid data, take help from some other notes

DAY-11

DAY-12

DAY-13

  • learn about data cleaning from linkedin

DAY-16

<script src="https://gist.github.com/ukantjadia/1ebc4e77b019242b0ccb2ebeca82a78b.js"></script>

DAY-17

  • Completed the EDA project with Covid-19 data

DAY-18

DAY-19

DAY-25

  • internshala certificate link link
A little progress each day adds up to significant results!
I am Elated to share my recent accomplishment of completing the Data Science training from Internshala Trainings powered by Analytics Vidhya. I am thrilled to share my accomplishment with my network. I have gained a wealth of knowledge and hands-on experience in the field. I am excited to share my skills and make a positive impact through data-driven projects.


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