Pinned Repositories
Algorithmic-trading-using-Averages-of-30-and-averages-of-100-days
Colaborative-Filtering
This is the way, companies like Amazon show you suggestions based on your likes.
Content-Based-Filtering-using-KNN-clustering-algorithm
we have a dataset of nearly 2 lakh movies which are grouped on the based of genre like action,adventure,comedy,etc. In this project we will be using KNN clustering {K nearest neighbors is a simple algorithm that stores all available cases and classifies new cases based on a similarity measure (e.g., distance functions)}. Here we will be recommending movies which have similar genre. NO ratings are involved so there wont be any noise so no need to look for outliers.
CoronaVirusVisualization
Covid-19-Data-Visulaization
DME-Project
DME-project-CAD
DOM-Project
Portfolio-Optimzation-in-Python
I built a hypothetical portfolio of stocks NFLX, TSLA, AAPL, FB, SPOT and tried to optimize the distribution between various stocks so that we can find the optimal RETURNS with least volatility(risk) ie higher sharpe ratio. i analyzed the % of daily returns as well as covarience of these stocks over each other. Finally i used PYPORTFOLIOOPT to optimize the hypothetical portfolio that i created...
SALES-ANALYSIS
SALES ANALYSIS OF A US BASED MULTI CHAIN ELECTRONIC STORE
sanchit15121999's Repositories
sanchit15121999/Colaborative-Filtering
This is the way, companies like Amazon show you suggestions based on your likes.
sanchit15121999/Content-Based-Filtering-using-KNN-clustering-algorithm
we have a dataset of nearly 2 lakh movies which are grouped on the based of genre like action,adventure,comedy,etc. In this project we will be using KNN clustering {K nearest neighbors is a simple algorithm that stores all available cases and classifies new cases based on a similarity measure (e.g., distance functions)}. Here we will be recommending movies which have similar genre. NO ratings are involved so there wont be any noise so no need to look for outliers.
sanchit15121999/Portfolio-Optimzation-in-Python
I built a hypothetical portfolio of stocks NFLX, TSLA, AAPL, FB, SPOT and tried to optimize the distribution between various stocks so that we can find the optimal RETURNS with least volatility(risk) ie higher sharpe ratio. i analyzed the % of daily returns as well as covarience of these stocks over each other. Finally i used PYPORTFOLIOOPT to optimize the hypothetical portfolio that i created...
sanchit15121999/SALES-ANALYSIS
SALES ANALYSIS OF A US BASED MULTI CHAIN ELECTRONIC STORE
sanchit15121999/Algorithmic-trading-using-Averages-of-30-and-averages-of-100-days
sanchit15121999/CoronaVirusVisualization
sanchit15121999/Covid-19-Data-Visulaization
sanchit15121999/DME-Project
sanchit15121999/DME-project-CAD
sanchit15121999/DOM-Project
sanchit15121999/Earthquake-prediction-using-Cat-boosting-and-SVM-algorithm
sanchit15121999/Netfilx-recommendation-system
In this project i tried to build a recommendation system just like netflix. To personalize the experience we will require the data of user and a user id so that we can add a separate feature of recommendation as per the shows/movies they have already rated. The recommendation that we are giving will be based on the similarity in genre of movies. It can also be based on the cast of movie or the director of movie. {{Country states that the content ws taken from which country}}
sanchit15121999/Portfolio-Management-Risk-Analysis-
sanchit15121999/Stock-closing-price-prediction
predicted the closing price of apple
sanchit15121999/Stock-Price-PREDICTION
PREDICTED AND BACKTESTED APPLE'S STOCK FROM 2008 TO 2020
sanchit15121999/Thermal-stress-aalysis-of-disc-brake-rotors-
sanchit15121999/Uber-New-York-analysis-for-2014-April-to-Sept
Descriptive Analysis of Uber Data