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2018-cycle-2

Contents covered in sessions of AI Saturdays (cycle 2) as well as relevant material for further study.

ai6-assignments

Official AI6 Bangalore Assignment Repository

brainfuck

A simple BrainFuck interpreter in Python

cg-mini-project

VTU 6th sem mini project for Computer Graphics

colornet

cosmos

[Show :heart: love by 🌟] Your personal library of every algorithm and data structure code that you will ever encounter

eip-2

External Internship Program @ The Inkers

eva5

fastai

The fast.ai deep learning library, lessons, and tutorials

hello-world

Getting started with GitHub!!!

hello-world-1

manga-downloader

A web scraping python script to download manga

mvitbyte

pytorch

question-the-pixels

A Visual Question Answering project that takes an input image along with a natural language question and outputs an answer to the question based on the contents of the image

reinforcement-learning-td3

Implement TD3 algorithm to train a car to move across two destinations in a map

sentimentanalysis

setosa

"Hello World" of Data Analytics

sih

Comparision of human voice samples

sih2018problemstatements

A Python Script for Scraping All the Smart India hackathon Problem Satements with Their Description

speech-emotion-recognition

Detecting emotions using MFCC features of human speech using Deep Learning

ulmfit_reproduce

ULMFiT results

vtu-students-marks-predictor

This project is aimed at predicting a student's Semester Grade Point Average in the consequent semester based on the LINEAR REGRESSION . The two algorithms that are used are Gradient descent which is a first-order iterative optimization algorithm. Feature Normalization or Feature Scaling which is used to standardize the range of of independent variables. On running these algorithms against the dataset it was observed that there is a correlation between students abilities in individual semester with the final overall academic performance. It can be ascertained that the abilities and strong engineering fundamentals are strong factors in influencing the overall academic performance. This prediction model could be used by the student as an extensive guide to carefully pan out the effort that he/she must incorporate in order to score superlative grades in the next semester.