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amazon-emplyee-access

This was a machine learning project where we would predict whether the person is amazon employee or not.

attend

A ionic app to mark attendance via facial recognition.

boosting-and-bagging-works

This would show the boosting and bagging techniques in machine intelligence where we have used Gradient Descent Optimizer and Random forests.

chemical-working-prediction

We have collected a huge data of chemical from chemical analyzing factory and has predicted whether the collected chemical is working or not.

cipher

This repo contains the solution to the crypto task given by Prof Ragesh Aggarwal of IITD in the course CON101.

data-cleaning-works

This was an assignments given to us on data cleaning

data-processing-works

This was a practice section for data science

hand-writing-recognition

We have used in-built libraries of Spyder and Jupyter Notebook for gathering the data and recognizing the human written hand digits using MNIST.

imdb-user-review-opinion-analysis

inventory-management-system

k-means-clustering

This was an assignment done by us to practice K-means clustering

label-encoding

learn_machine_learning_in_3_months

This is the code for "Learn Machine Learning in 3 Months" by Siraj Raval on Youtube

letters-prediction-model

This model works on Support Vector Machine to predict the letters written by user.

linear-regression-problems

Here this project consists of problems that are solved using linear regression. Boston Problem, Computer Dataset Problem, Concrete Data Problem, Iris Problem, Video Games Global Sales, and found traces and relation between years of experience and salary...

mtcars

K-Nearest Neighbors were used to classify the data of cars....

nba-records-analysis

This was a data analysis project on NBA Records.

nba-selection-prediction-model

Here this model would predict whether the candidate would be selected for NBA or not by using Logistic Regression.

population-growth-prediction

We have made a machine learning model which will predict the population growth of selected countries in different years. We have collected data from Internet.

practice-on-deep-intelligence

In this sessions, we have implemented deep learning techniques using TensorFlow and Keras along with other packages like Pandas, Numpy etc. We have been testing the power of deep learning using our project as a platform

rms-titanic-survival

This was a practice for machine intelligence models where data of titanic survivals was taken from Kaggle and performed various operations on it. We have chosen an algorithm which would get higher efficiency.

spotify-data-classifier

We have collected a huge amount of data from Spotify and has used various classification machine intelligence techniques to classify them. At last we have used Decision Trees algorithm, which has given us better results.

stocks-prediction-and-performance

We have collected a huge data on stocks from google finance and has applied machine intelligence to predict the stock price in future time. We have tried Regression algorithms on the data to get the better performance.

tester

text-summarization

In this project user would give huge passage to machine and the machine could generate Summary of the passage using machine intelligence

twitter-analysis

This model is used to predict the sentiment using opinion analysis technique for data collected from Twitter.

uber-data-analysis

We have collected the data of Uber from Internet and then made a detailed analysis of trends set by uber. This project consists of various graphs which declare the trends set by uber.