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adult_income

Analyze features related to adult income using multiple machine learning models.

apps_case_study

Analyze whether there is a significant difference between the ratings on the Apple Store vs Google Play.

auto_advisor-java-angularjs-springmvc

aws_deepracer-object_avoidance

Train and evaluate reinforcement learning models using autonomous vehicles in AWS DeepRacer to avoid objects.

basic_calculator

Mouse, touch, keyboard, and numeric keypad inputs are accepted.

bayesian_optimization_case_study

Visualize a Bayesian parameter optimization in Python for a Light GBM model.

big_data-pyspark_and_databricks

Use PySpark DataFrames, SQL, and MLlib to construct classification models on Databricks.

blackjack_online

blackjackproject

Blackjack Poker

building_a_recommendation_system

Pydata hands-on tutorial teaches you how to create a basic recommendation system in Python.

chatbot-pytorch-nlp-deeplearning

Helper escalation chat bot that trains on deep learning models to help answer questions.

clustering_case_study

Implement the K-Means clustering algorithm, find the value for K using the Elbow method, the Silhouette method, and the Gap statistic, and visualize the clusters with Principal Components Analysis (PCA).

cosine_similarity

Explore the utility of cosine similarity for record matching and NLP projects.

decision_tree_specialty_coffee

Use scikitlearn to build four different decision tree models, two using entropy and two using gini impurity, to ascertain whether a potentially business-transforming deal will take your business to the next level.

eshoponcontainers

A reference .NET application implementing an eCommerce site

euclidean_and_manhattan_distances

Apply Euclidean and Manhattan distances and visualize their results.

featuretools

Adapted exercise from here: https://github.com/Featuretools/predict-customer-churn/blob/master/churn/3.%20Feature%20Engineering.ipynb

financial-demo

A demo for a financial services bot

frequentist_case_study

The Pythonic implementation of the concepts underlying frequentist inference and applying them to a real-world scenario.

gradient_boosting-titanic

How gradient boosting works to improve predictions based on information from the residuals.

grid_search_knn_case_study

Identify the optimal number of neighbors to use in the K-nearest neighbor model.

grocery_recommender

Research what type of machine learning models provide the most accurate recommendations.

linear_regression_case_study

This case study uses linear regression to explore which red wines have properties that make them more alcoholic.

logistic_regression_advanced_case_study

Case study to work through the math behind logistic regression.

london_housing_case_study

Data science analysis on housing prices.

pluralsight-designing-react-components-course-code

Pluralsight Course on Designing React Components.

predicting_credit_card_approvals

Build a machine learning model to predict if a credit card application will get approved.

pycon-2016-tutorial

Machine Learning with Text in scikit-learn

quandl_financial_data_api_mini_project

Integrating with a public FNCE API to get requests and filter json and dictionary data.

randomforest_covid_case_study

Use Random Forest and logistic regression to understand the scope of the Coronavirus.