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C CHARAN TEJA's Projects

datacamp icon datacamp

A repository that contains courses I have taken on DataCamp

datasist icon datasist

A Python library for easy data analysis, visualization, exploration and modeling

deep-learning-1 icon deep-learning-1

Implementation of Deep Learning Algorithms and useful information (courses, books, videos, etc.)

digit-recognizer-with-python icon digit-recognizer-with-python

We used preprocessing programs made available by NIST to extract normalized bitmaps of handwritten digits from a preprinted form. From a total of 43 people, 30 contributed to the training set and different 13 to the test set. 32x32 bitmaps are divided into nonoverlapping blocks of 4x4 and the number of on pixels are counted in each block. This generates an input matrix of 8x8 where each element is an integer in the range 0..16. This reduces dimensional and gives in-variance to small distortions.

eda-automobiles icon eda-automobiles

Exploratory Data Analysis of the Automobile Data Set - UCI Machine Learning Repository - Data Science with Python - UPX Academy

examples icon examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

exploration icon exploration

Science des Données Saison 2: Exploration statistique multidimensionnelle, ACP, AFC, AFD, Classification non supervisée

googlemaps-fastest-route icon googlemaps-fastest-route

A simple fastest route finder written in Java includes BFS, Djikstra(Speed limits included) and A* Algortihms also has the feature of visualization of visited nodes.

great-lakes icon great-lakes

This is a collection of the different Machine Learning & Deep Learning Projects undertaken by me. Some of these projects are part of the PGP AI-ML course from Great Lakes Institute of Management, to which I am currently enrolled to

hackerrank icon hackerrank

A collection of algorithms and solutions to problems in various languages from the site Hacker Rank.

high-dimensional-deep-learning icon high-dimensional-deep-learning

Science des données Saison 4 : Apprentissage en grande dimension, Données fonctionnelles, Détection d'anomalies, Introduction au Deep Learning

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