jasoncaldwellmba Goto Github PK
Name: Jason Caldwell
Type: User
Company: Senior Software Engineer
Location: Colorado Springs, CO
Name: Jason Caldwell
Type: User
Company: Senior Software Engineer
Location: Colorado Springs, CO
Analyze features related to adult income using multiple machine learning models.
Analyze whether there is a significant difference between the ratings on the Apple Store vs Google Play.
Train and evaluate reinforcement learning models using autonomous vehicles in AWS DeepRacer to avoid objects.
Mouse, touch, keyboard, and numeric keypad inputs are accepted.
Visualize a Bayesian parameter optimization in Python for a Light GBM model.
Use PySpark DataFrames, SQL, and MLlib to construct classification models on Databricks.
Blackjack Poker
Pydata hands-on tutorial teaches you how to create a basic recommendation system in Python.
Helper escalation chat bot that trains on deep learning models to help answer questions.
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).
Explore the utility of cosine similarity for record matching and NLP projects.
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.
A reference .NET application implementing an eCommerce site
Apply Euclidean and Manhattan distances and visualize their results.
Adapted exercise from here: https://github.com/Featuretools/predict-customer-churn/blob/master/churn/3.%20Feature%20Engineering.ipynb
A demo for a financial services bot
The Pythonic implementation of the concepts underlying frequentist inference and applying them to a real-world scenario.
How gradient boosting works to improve predictions based on information from the residuals.
Identify the optimal number of neighbors to use in the K-nearest neighbor model.
Research what type of machine learning models provide the most accurate recommendations.
This case study uses linear regression to explore which red wines have properties that make them more alcoholic.
Case study to work through the math behind logistic regression.
Data science analysis on housing prices.
Pluralsight Course on Designing React Components.
Build a machine learning model to predict if a credit card application will get approved.
Machine Learning with Text in scikit-learn
Integrating with a public FNCE API to get requests and filter json and dictionary data.
Use Random Forest and logistic regression to understand the scope of the Coronavirus.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.