# Github

<span class="break-words
      "><span class="text-view-model" dir="ltr">1. Turn Data and AI algorithms into production-ready web applications with Python in no time - [https://lnkd.in/eCckCG75](https://lnkd.in/eCckCG75)  
  
2\. All Algorithms implemented in Python - [https://lnkd.in/eEU8uNkZ](https://lnkd.in/eEU8uNkZ)  
  
3\. Data science Python notebooks - [https://lnkd.in/d6rE2PNc](https://lnkd.in/d6rE2PNc)   
  
4\. Learn Ptyhon - [https://lnkd.in/e3dgvHZw](https://lnkd.in/e3dgvHZw)  
  
5\. Practice your pandas skills - [https://lnkd.in/dFuzqRKh](https://lnkd.in/dFuzqRKh)  
  
6\. 100 Days of ML Coding - [https://lnkd.in/eikbh9Pb](https://lnkd.in/eikbh9Pb)  
  
7\. Awesome Python - [https://lnkd.in/ewN\_kNPx](https://lnkd.in/ewN_kNPx)  
  
8\. Stanford's CS 229 Machine Learning - [https://lnkd.in/dtYkbVjt](https://lnkd.in/dtYkbVjt)  
  
9\. MIT Deep Learning - [https://lnkd.in/dhFcvbb5](https://lnkd.in/dhFcvbb5)  
  
10\. Data Analysis and ML Projects - [https://lnkd.in/dSAGFeZY](https://lnkd.in/dSAGFeZY)  
  
11\. Data Science related questions and answers - [https://lnkd.in/d-34wtwx](https://lnkd.in/d-34wtwx)  
  
12\. 120+ interactive Python coding interview challenges - [https://lnkd.in/eMq2zicJ](https://lnkd.in/eMq2zicJ)  
  
13\. 300 Python Interview questions with solutions - [https://lnkd.in/eKxZdc9n](https://lnkd.in/eKxZdc9n)  
  
14\. Data Science Interview Resources - [https://lnkd.in/eAKnpQm9](https://lnkd.in/eAKnpQm9)  
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