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30-days-of-python

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.

accuracy-of-enterprise-data-using-ml

We will be taking a dataset to predict that whether customer is going to buy a particular product or not by training the data model. We will be using Binary Classification to get the decision of customer. Cloud will be taking care of all complexity by running all process over the provided resources instead on the user’s system.

array-1

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backend

Contributing to open source can be a rewarding way to learn, teach, and build experience.

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bactracking-1

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binary-search-1

binary-search-2

binary-search-3

binary-search-4

bus_reservation_master

chrome-web-speech-api

Chrome Web Speech API

competitive-coding-4

competitive-coding-5

competitive-coding-6

competitive-coding-8

crop_prediction_using_ml

The designed hybrid neural network model identifies optimal combinations of soil parameters and blends it with the rainfall pattern in a selected region to evolve the expectable crop yield. The backbone for the predictive analysis model with respect to the rainfall is based on the Time-Series approach in Supervised Learning. The technology used for the final prediction of the crop yield is again a branch of Machine Learning, known as Recurrent Neural Networks. With two inter-communicating data-driven models working at the backend, the final predictions obtained were successful in depicting the interdependence between soil parameters for yield and weather attributes.

data-structures-algorithms-python

This tutorial playlist covers data structures and algorithms in python. Every tutorial has theory behind data structure or an algorithm, BIG O Complexity analysis and exercises that you can practice on.

datastructures-algorithms

The best library for implementation of all Data Structures and Algorithms - Trees + Graph Algorithms too!

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design-2

design-3

dfs-2

docker-cheat-sheet

Docker Cheat Sheet

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