ShrishtiHore/Kaggle-Sucide_Analysis_Problem_1985-2016

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ShrishtiHore/Kaggle-Sucide_Analysis_Problem_1985-2016

ShrishtiHore

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In this problem a compiled dataset pulled from four other datasets linked by time and place, and was built to find signals correlated to increased suicide rates among different cohorts globally, across the socio-economic spectrum. This is with an aim to understand global suicide and take necessary actions in areas required💫🚫⚰📊📈⌛.

Conversational_Chatbot_using_LSTM

This project is to create conversational chatbot using Sequence to sequence LSTM models. Sequence to sequence learning is about training models to convert from one domain to sequences another domain.🔊👾😎

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Anomaly-Detection-in-CCTV-Surveillance-Videos

This projects detect Anomalous Behavior through live CCTV camera feed to alert the police or local authority for faster response time. We are using Spatio Temporal AutoEncoder and more importantly three models from Keras ie; Convolutional 3D, Convolutional 2D LSTM and Convolutional 3D Transpose. 👮‍♂️👮‍♀️📹🔍🔫⚖

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Weapons-Detection-in-Real-Time-Surveillance-Videos

This project aims to minimize the police response time by detecting weapons through a live CCTV camera feed. So it alerts the police as soon as it detects any sort of weapons. In our project we are focusing on guns primarily. 🔫💣💻🎥

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Quantium_Virtual_Experience_Program

This repository is a collection of all the solutions of tasks that were assigned to me during my Data Analytics Virtual Internship Experience Program at Quantium. 💻📚📊

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Retail_Global_Customer_Analysis

The Super Store dataset contains data on order details of customers for orders of a superstore ie; chain of multiregional stores under a brand globally. This is a detailed analysis on customer behavior analysis.

Target_Brazil_Sales_Analysis

Target is one of the world’s most recognized brands and one of America’s leading retailers.This business case has information of 100k orders from 2016 to 2018 made at Target in Brazil. Its features allows viewing an order from multiple dimensions.

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HR-Employee-Attrition-Analysis

Employee attrition analytics is specifically focused on identifying why employees voluntarily leave, what might have prevented them from leaving, and how we can use data to predict attrition risk.

Deep-Dream-using-Tensorflow

Deep Dream is a computer vision program created by Google which uses convolutional neural networks to find and enhance patterns in images thus creating a dream like hallucinogenic apppearance in the deliberately over_processed images. 🎭🖼🎨⚗💊💉

Text_Generator_And_Artificial_Copy_Editor

Artificial Text predictor based on RNN LSTM method can predict text in any language. The AI based text editor can create new transcripts based on a sample literature of any writer and in any language.

Twitter_Sentiment_Analysis

Using Twitter Developer API build a Sentiment Analyzer to give check if the emotions of users regarding the topics are positive, negative or neutral using their tweets by method of tokenization and Bag of Words algorithm.🎭🔊⚖📳🙂😐☹

Ecommerce_Sales_Analysis

Successful ecommerce businesses need to optimize every stage of the customer journey, from first touch to purchase. This ecommerce dashboard is a curated set of metrics, KPIs and other data that’s designed to highlight, in the clearest possible way, trends, anomalies and information related to an online store that regularly warrants attention.

Auto-Neural-Translator-English-to-Marathi

Machine translation refers to translating phrases across languages using deep learning and specifically with RNN (Recurrent Neural Nets). Most of these are complex system that is they are combined system of various algorithms. But, at its core, NMT uses sequence-to-sequence ( seq2seq ) RNN cells. Such models could be character level but word level models remain common. ✏🧾📚📰🖋🎤

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AWS_Self_Driving-Car-AWS_DeepRace_2019

In 2019 I participated in Amazon Web Services Deep Race Competition in Re:Invent event held every year. I had selected the Toronto Turnpipe Roadmap for simulating my DeepRacer Bot. simulating it using AWS Robomaker and AWS Sagemaker by tuning hyperparameters like track width, degrees of freedom, steer angle and track type. Fastest time to complete laps 1:13 secs with 0.978 Accuracy in Toronto Turnpipe Track field .🖥🚗🛣🕖↩

TakenMind_Internship

A repository for all the weekly assignments done during my 1 month internship in TakenMind along with the Final Project and their documentation.📈📉📊📐

Competitive_Problems

My everyday competitive programming practice to keep my coding and problem solving skills on the edge always !!!

AB-Testing-and-Predictive-Analysis-for-New-Menu-Launch-using-Alteryx

The coffee restaurant will test a new menu in Denver and Chicago using TV ads to see if it boosts profits by at least 18%, justifying the marketing costs, and needs an analysis to decide on a wider rollout.

Hackerrank_30_Day_Code_Challenge

Series of 30 problems from basic to complex as a challenge. (C prorgramming)

Predicting_Stock_Prices

This project aims to predict stock prices using Scikit-learn library and plotting a graph using Matplotlib.📈📊📉📋📆💰

Seattle-and-Boston-AirBnB-Comparison

Data Analysis in Python on the effects of AirBnB home properties on prices in the west and east coasts (such as no. of beds, location, property type, revi ews) and compare them.

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Genetic_algorithms

In this demo code we use the MAGIC Gamma Telescope dataset to build a classifier. The classifier will train on the dataset and then be able to classify whether or not some energy is either Gamma Radiation or Hadron Radiation.🔥🧩🔋

Labour-Data-Forecasting-and-Analysis

Tableau and MS Excel based project anticipates no. of hours an Australian business will need its employees to work in future. Predictive analysis on variety of inputs for future behaviour.

A-B-Testing-Analysis

As players progress through the game they will encounter gates that force them to wait some time before they can progress or make an in-app purchase. In this project, we will analyze the result of an A/B test where the first gate in Cookie Cats was moved from level 30 to level 40.

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Text_Classification_using_LSTM

This project is made to classify sentiments in IMDB movie reviews. 🎞🎟🎫🎭📽🎬📺☹😊

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Financial_Analysis

Financial analysis is not only to be done in the planning stages of a project, but throughout every stage of the project throughout the duration of the project. Top 5 elements : Revenue, Operations, Profits, Capital, Liquidity.

Cryptocurrency-Analysis-Buy-and-Hold

Time series prediction and risk analysis in Python to find out which coin (Bitcoin, Ethereum, Bitconnect or Dogecoin) would be most profitable to invest on using buy and hold strategy.

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Credit-Card-Fraud-Detection

Machine learning project to detect potential fraud transactions so that the customers are ensured that they won’t be charged for items they did not purchase by building 6 types of classification models and classifying fraud transactions from non-fraud transactions.

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Corrosion_Resistance

This project was a part of my tasks during my internship at Stir Research. The project consisted of various data exploratory analysis and data visualizations to be carried out on the given data by the company. 📈📉📊📋📚⚔🔬⚒🛠⚙⛏🔧

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Customer_Grading_System

Develop a customer grading schema for an offline retail store. This exercise is to help us understand who our most loyal customers are and who are not. You may use as many metrics you believe that are relevant to get an accurate result. Keywords: SQL, Tableau, Data analysis, Business analytics, DBMS

FDI-case-study-analysis

Data Analysis on Indian FDI (Foreign Direct Investment) dataset from the perspective that a company will benefit in which sector to work with using Tableau. Data cleaning and pre-processing done in MS Excel. It also has forecast option to predict future values

IMDB-movies-data-analysis-dashboard

This Tableau dashboard was created to analyse and compare various directors, actors, movies, genres, and content ratings from IMDB data and the data wrangling was done using MS Excel.

Kaggle-_Titanic_Survival_Competition

This is the legendary Titanic ML competition – the best, first challenge for you to dive into ML competitions and familiarize yourself with how the Kaggle platform works. The competition is simple: use machine learning to create a model that predicts which passengers survived the Titanic shipwreck.⛵🛥🚢🚏⚓

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Amsterdam-AirBnB-Analysis-story

Python project that performs data exploration on fields such neighbourhoods, room types, accommodates, etc. and gives advice to the municipality of Amsterdam to curb illegal hotel bookings and helps tourists to find a good AirBnB host using interactive Folium maps, interactive plotly graphs, and Sentiment Analysis (NLP - text mining) of review comments.

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Sales-Insights

This project provides sales insights to computer hardware business company Atliq Technologies which is facing challenges in dynamic market and provides advice to resolve them by creating an in-depth data analysis dashboard in Tableau. The initial data cleaning and data exploration was done using SQL on the data from the company’s real-time database.