Playmen998/Psychotype_Bot

Телеграмм бот, который предсказывает тип психотипа по методике MBTI

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rivas-j/Cryptocurrency-Investment-Portfolio_Data-Science

Data Science Driven Cryptocurrency Investment Portfolio

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ashwinihegde28/Cryptocurrencies

Unsupervised Learning

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shayleaschreurs/Machine-Learning-Trading-Bot

Our goal was to create a ML bot that analyzes real time trading data to determine the most opportune times buy and sell stock

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mmsaki/san_fransisco_real_estate

An application of technology to real-estate markets, is an innovative domain in the fintech industry. Assume that you’re an analyst at a proptech company that wants to offer an instant, one-click service for people to buy properties and then rent them. The company wants to have a trial of this offering in the San Francisco real-estate market.

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lingumd/US_Natural_Disaster_Analysis Fork of jeaninemjordan/US_Natural_Disaster_Analysis

A thorough analysis studying the correlations and patterns of natural disasters across time and region in the United States using Python.

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Analitico-771/grayscale_analysis

This is an application that fetches historical data on 1 index, 4 stocks, and 2 crypto currencies and performs analytical calculations to assist in conducting a relative analysis between the index and the crypto currencies to determine if a relationship exists and the type of relationship for the purpose of conducting portfolio analysis and Monte Carlo Simulation for forecasting potential future returns.

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lingumd/Cryptocurrencies

Unsupervised machine learning models used to group the cryptocurrencies to help prepare for a new investment.

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twigikit/PyViz-homework

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eric-blankinshp/Cryptocurrencies

Cryptocurrency data is preprocessed using Pandas to fit Unsupervised Machine Learning models. A clustering algorithm is used to group data. hvPlot visualization are used to share results.

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fischlerben/San-Fran-Housing-Market-Visualizations

This project utilizes Python visualizations packages, such as Plotly Express, HVPlot and PyPlot/Matplotlib to create an interactive dashboard exploring the San Francisco real estate housing market. Uses MapBox API.

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sh-4/Cryptocurrencies

The purpose of this analysis is to look at what cryptocurrencies are on the trading market and how they could be grouped together to create a classification system for a potential investment.

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shayleaschreurs/Real-Estate-Value-Finder

This is a collaboration with two classmates to create a program that shows us some of the best valued homes in any city or neighborhood by analyzing and sorting data of comparables using the Reality Mole API. We then created graphs using hvplot to easily visualize which homes in the area show the greatest investment potential.

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shayleaschreurs/Time-Series_Analysis

Module 11 - I will be creating a visual depiction of seasonality (as measured by Google Search traffic), an evaluation of how the company stock price correlates to Google Search traffic, A Prophet forecast model that can predict hourly user search traffic, and a plot of a forecast for the company’s future revenue.

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shayleaschreurs/Unsupervised_learning

Module 10 - Using python programming and unsupervised learning, I am creating a notebook that clusters cryptocurrencies by their performance in different time periods. Then I will plot the results for a better visual

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shayleaschreurs/Python_Data_Visualization

Module 6- I am creating an analysis of the housing rental market data for San Francisco. The analysis will be complete with professionally styled and formatted interactive visualizations.

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tyedem/Machine-Learning-Trading-Bot

Backtesting machine learning trading strategies with multiple supervised learning models and tunings for maximum profitability

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jmoletteire/Cryptocurrencies

Examining which cryptocurrencies are on the trading market and how they could be grouped to create a classification system for a potential investment.

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mudgalabhay/CO2_Emission_Dashboard

Interactive Dashboard of CO2 Emission

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bishopce16/cryptocurrencies

An analysis on cryptocurrencies dataset using unsupervised machine learning, PCA algorithm, and K-means clustering.

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SohaT7/Cryptocurrencies

Unsupervised machine learning algorithms (PCA dimensionality reduction and K-means clustering algorithm) report on tradable cryptocurrencies and create a classification system for them, using Scikit-learn, Pandas, Plotly, and hvPlot in Python.

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Gsilvera24/Time-Series-Analysis-using-Facebook-Prophet

Time Series Analysis and FB Prophet Analysis.

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Wamuza1/Cryptocurrencies

Analysis of crypto data for the investors who are preparing to get into the cryptocurrency market.

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akthersr/Cryptocurrencies

In this analysis we uses unsupervised machine learning on a dataset of cryptocurrencies and classify them into a few groups according to their features.

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ksommerdorf/UnsupervisedML

Case study utilizing unsupervised machine learning.

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annakthrnlee/Cryptocurrencies

Using unsupervised machine learning, I created a report that includes what cryptocurrencies are on the trading market and how they could be grouped to create a classification system for this new investment.

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olesyapro888/Cryptocurrencies_Analysis_Unsupervised-ML_scikit-learn_PCA_K-means

The analysis of the cryptocurrency market is based on unsupervised machine learning with preprocessed data, reduced dimensions using PCA, clustered data using K-means.

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lrb924/Housing_Rental_Analysis

Housing Rental Analysis for San Francisco

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lrb924/Forecasting_Net_Prophet

Forecasting Net Prophet

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emaynard10/Cryptocurrencies

Unsupervised machine learning to preform principal component analysis, and use clustering to determine trends in different crytocurrencies.

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StrawhatRA/TO-Real-Estate-Analysis

Toronto Real estate analysis dashboard with interactive visualizations to explore investment opportunities.

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theodcr/corregraphe

💃 Correlation graphs with NetworkX

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teachjanderson/Cryptocurrencies

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m-miley/Cryptocurrencies

Unsupervised Machine Learning Analysis to identify classes of cryptocurrencies using K-Means Clustering and implementing PCA to reduce dimensionality.

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shumph10/Cryptocurrencies

Unsupervised machine learning was used to establish a classification system for actively trading cryptocurrencies for potential investment prospects.

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mdbinger/Cryptocurrencies

Preprocessed cryptocurrency dataset for Principal Component Analysis. Ran K-means algorithm to predict the optimal amount of K clusters for algorithm. Built table of currently tradable cryptocurrencies using hvplot.table function.

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lukee11/Capstone_Project_Group_B

Algorithmic trading and quantitative testing

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rajimuth/Cryptocurrencies

Unsupervised Machine Learning for Cryptocurrency Analysis

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nssensalo/global-crypto-behavior Fork of Fintech-Collaboration/global-crypto-behavior

A visualization index designed to analyze fluctuations in crypto exchange data as it correlates with global crypto-specific news stories sentiment data

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tyedem/Suspicious_Transactions

Financial fraud analysis utilizing data modelling and engineering techniques to identify suspicious transactions

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tyedem/Toronto-Real-Estate-Analysis

Real estate analysis dashboard with interactive visualizations to explore investment opportunities

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Analitico-771/machine_learning_trading_bot

This is an Application that implements an algorithmic trading strategy that uses machine learning to automate the trade decisions

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Analitico-771/forecasting_mercado_libre

This is an application that can be used to analyze company's financial and user data in clever ways to identify areas to improve and help the company grow. So, you want to find out if the ability to predict search traffic can translate into the ability to successfully trade the stock

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wattsr1/Neural-Network-Charity-Analysis

Analysis for fund use of Nonprofit organizations

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wattsr1/Cryptocurrencies

Analysis of various cryptocurrencies using unsupervised machine learning

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asia-rahman/quanititative_analysis

This app helps you determine the fund with the most investment potential based on key risk-management metrics: the daily returns, standard deviations, Sharpe ratios, beta, etc.

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Analitico-771/etf_analyzer

This is an An application that pulls and analyzes ETF data from a database

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Analitico-771/financial_health_planner

This App helps you evaluate your financial health and its broken down into two planning strategies.

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Analitico-771/housing_rental_analysis

The main objective of this App is to visualize and analyze the housing rental market datafor San Francisco into the below areas so that a person can make an investment decision. For example, you can look for areas that demand high $$ for rent but you can buy at a lower sale price per square foot.

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benjaminweymouth/SQL-Fraud-Transactions-Analysis

This repo is a postGRESQL and fraud finding techniques

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MUSA-550-Fall-2020/philadelphia-shootings-app

A Panel-based dashboard showing recent shootings in Philadelphia using Altair, Folium, and Hvplot

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MUSA-550-Fall-2021/week-14

Dashboarding with Panel and the Holoviz Ecosystem

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MUSA-550-Fall-2021/philadelphia-shootings-app

A Panel-based dashboard showing recent shootings in Philadelphia using Altair, Folium, and Hvplot

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MUSA-550-Fall-2021/week-4

More Interactive Data Viz, Working with Raster Data

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MUSA-550-Fall-2021/week-7

Analyzing and Visualizing Large Datasets

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nicoserrano/Cryptocurrencies

Cryptocurrencies analysis using unsupervised machine learning and Python

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SindieCastro/Cryptocurrencies

Used unsupervised machine learning model to explore cryptocurrency data

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Jacqueline-Esbri/Cryptocurrencies

Used Unsupervised Machine Learning to Analyze Cryptocurrency Data

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jharvey09/Cookies_Crumble_but_CryptoCurrency_Clusters

In this project, the tools used are unsupervised learning (K-Means Clustering) accompanied by 3-D HVPlot visualizations to group cryptocurrencies by feature

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MUSA-620-Fall-2019/philadelphia-shootings-app

A Panel-based dashboard showing recent shootings in Philadelphia using Altair, Folium, and Hvplot

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aliciasply/Final-Project

Fake News! Detector aims to find a way to weed out the real news from the fake news. We create this machine learning model to identify authentic news from the swam of fake news on social media.

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amylio/Cryptocurrencies

An analysis using unsupervised Machine Learning algorithm to discover unknown patterns.

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AaronGalloway/unit13-challenge

Clustering Crypto. A project that explores the following areas: Pandas DataFrames, Data Cleaning, Scaling Data, K Means, Principal Component Analysis, hvPlot, and 3-D Plotting

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MUSA-550-Fall-2020/week-14

Dashboarding with Panel and the Holoviz Ecosystem

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MUSA-550-Fall-2020/week-7

Analyzing and Visualizing Large Datasets

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MUSA-550-Fall-2020/week-4

More Interactive Data Viz, Working with Raster Data

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vmieres/Rental-Analysis-and-Dashboard

This repo is about a rental analysis for the San Francisco Market

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LiZhuang214/week-4 Fork of angelicakim28/week-4

More Interactive Data Viz (pyViz), Getting Started with APIs

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LiZhuang214/assignment-3 Fork of jklion/assignment-3

Materials for the assignment #3

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maitree7/Rental_Analysis

Rental Analysis using PyViz

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Kowsi/Real_Estate-Rental_Analysis

Rental Analysis using PyViz

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MUSA-620-Fall-2019/week-14

Dashboarding with Panel and the Holoviz Ecosystem

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