Python solutions to solve practical business problems.

Overview

Python Business Analytics


Also instead of "watching" you can join the link-letter, it's already being sent out to about 90 people and you are free to join too. I will start sending it out to the public by November 2019. Monthly link-sharing list: https://mailchi.mp/0c1fd456af3b/firmaipython

Intermediate to Advanced


A series looking at implementing python solutions to solve practical business problems. Share your own projects on this subreddit, r/datascienceproject. Every week we will look at hand picked businenss solutions. See the following google drive for all the code and github for all the data. If you follow the LinkedIn page, you would be able to see the lastest developments.


All projects are of intermediate to advanced difficulty and the projects are not presented in any particular order; nothing stops you from starting at week six for example.

Week 1/52: Bike Share Business Case - Google Colab

Outlier Analysis, Model Selection, Missing Values, Descriptive Statistics

Week 2/52: Reuters Author NLP - Google Colab

Process Text, pyLDAvis, Word Embeddings, Text Evaluation, fuzzywuzzy

Week 3/52: Customer Lifetime Value - Google Colab

RFM Analysis, Pareto Model, NDB Model, Gamma-Gamma Model, CLV Model, Constraint Programming

Week 4/52: Customer Segmentation - Google Colab

Radar, Silhouette, PCA, Grouping, Invoices, Inventory, Datatable, Basket,

Week 5/52: Customer Visits - Google Colab

Week, EDA, Simulated, Prediction, Dummy Variable

Week 6/52: Demand Forecasting - Google Colab

Neural Network, Sales, Relu, LSTM, CNN, Evaluation

Week 7/52: AirBnB Sydney Rent Evaluation - Google Colab

Full Pipeline, Random Forest, Visualisation, Grid Search, Confidence Interval

Week 8/52: Portfolio Optimisation - Google Colab

Efficient Frontier, Stocks, Modern Portfolio Theory, Pivot, Simulations, Minimum Volatility, Sharpe Ratio

Week 9/52: Economic Analysis - Google Colab

GDP, Life Satisfaction, Linear Regression Plots, Prediction Model

Week 10/52: Loan Classification - Google Colab

Default, Credit Scores, Visualisations, Data Cleaning, ROC Curves, Multi-class Classification

Week 11/52: Venture Capital - Google Colab

Capital Allocation, Decision Trees, Acquisitions, Investment

Week 12/52: Bankruptcy Prediction - Google Colab

Voting Classifiers, Bagging Ensembles, SMOTE, XGBoost, Cross-validation

Week 13/52: HR Analytics - Google Colab

OSEMN, Bagging Ensembles, AUC, Model Comparison, ROC Graph, Feature Importance Graph

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A next-generation curated knowledge sharing platform for data scientists and other technical professions.

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PowerApps-docstring is a console based, pipeline ready application that automatically generates user and technical documentation for Power Apps.

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Documentation and issues for Pylance - Fast, feature-rich language support for Python

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Code and pre-trained models for "ReasonBert: Pre-trained to Reason with Distant Supervision", EMNLP'2021

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Generates, filters, parses, and cleans data regarding the financial disclosures of judges in the American Judicial System

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BakTst_Org is a backtesting system for quantitative transactions.

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A Python library for setting up projects using tabular data.

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An introduction to hikari, complete with different examples for different command handlers.

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Python code for working with NFL play by play data.

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