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-python-in-just-10-program

In this repository you will get to know about all the concept of python in just 10 programs

ar

automata

bookshowwithtmdb

cat-and-dog-detection-using-cnn

compare-2-document

cookiewithjs

customer-behavior-analysis

datapreprocessing

BLOG ON DATA PREPARATION

decisiontree-vs-randomforest

In this model i have applied both decision tree and random forest on a data set and predict by the help of confusion matrix and classification report

demo-portfolio-website

A very simple portfolio website where you can find explanation to every line of code.

extractive-text-summarization

geeks_for_geeks_ios_app

google_stock_price_prediction_using_rnn

hacktoberfest

A collection of words! :star: it if you :+1: it !

handwritten-text-recognization

handwrittern-digit-recognition

handwritten digit recognizer trained on MNIST dataset

intro-to-data-science-in-python

Repo for the first course of the Applied Data Science with Python Specialization taught by University of Michigan hosted by Coursera

ios_youtube_playlist_app

mean-median-mode-using-c

In this program we will calculate mean,median mode of any array using c.

meansquarederror

netflix-reccomendation-system

This contains a data set in which there are negative as well as positive review.This project will separate the data set and carried out some index and at last user will get popularly recommended movies,series etc.

predicting-review-using-nlp

quora_classification

Quora is an American question and answer website where questions are asked and edited by the Internet users, in the form of opinions, which include questions that are harmful to our community, and should be removed before they have a chance to cause harm(or spawn imitators). The entire project would be consisting of predicting sincerity of questions on Quora. The dataset concerned here, consists of over 1.3 million questions, having the opportunity to train and test models, to detect insincerity and trolling based on real Quora questions. In conjunction with dataset, the project would be focused on solving this problem. We have used machine learning involving classification for the same. The entire project duration consists of training the available dataset with appropriate algorithms, to develop a model, and then testing the model with appropriate test dataset. The aim of the analysis is to provide a safe and legit content website for Quora's 300 million monthly users. Count Vectorizer model was developed for each question, which was then fitted to Logistic Regression model, which classified the unseen questions with about 91 % accuracy. Keywords: Quora, Insincerity , trolling, prediction, machine learning

selectionsort-using-c

In this repository selection sort has been explained and executed using c programming language.

sentence-generator-using-ngram

I have developed one character ngram and word ngram to generate a sentence. I have taken a very small dataset. After applying both the model i got to know that word ngram give more accurate result as compare to character ngram.

sentiment_analysis

I have done 2 types of sentiment analysis.

targetdeals

Architecture - VIPER

textsummarization

titanic-machine-learning-from-disaster

Predicting survival on the Titanic and get familiar with ML basics