dumbjarvis

dumbjarvis's Stars

• ShanteDenise/tech-interview-handbook

  💯 Algorithms, front end and behavioral content for rocking your coding interview 🆕 Interview Cheatsheet! 🆕

  64

• daddydrac/lightweight-ui-slider

  A lightweight 2 byte banner rotator that only uses 2mb of browser RAM

  Language:JavaScript2

• daddydrac/CMS-Template-Helper

  Custom CMS template helper plug in that dynamically adds css to the final child that is dynamically output from the dB

  2

• daddydrac/HomeworkTasksApp

  Teaching code for kids

  Language:CSS2

• daddydrac/IBM-Watson-Artificial-Intelligence-Developer-Certification-Study-Guide

  The certification exam covers all of the aspects of building an application that uses Watson services. This includes a basic understanding of cognitive technologies, as well as a practical knowledge of the core APIs.

  86

• daddydrac/SASS-CSS3-Animation

  SASS Example with CSS3 Animations

  Language:SCSS2

• daddydrac/Reinforcement-Learning-Contextual-Bandits

  2

• daddydrac/react-redux-d3-dashboard

  Example of how to use React, Redux, and D3 to make a DataScience dashboard

  Language:JavaScript31

• daddydrac/mapo

  Predict mining prospects and mineral deposits using deep learning and satellite imagery

  Language:Jupyter Notebook2

• daddydrac/kafka-fraud-detector

  🚨 Simple, self-contained fraud detection system built with Apache Kafka and Python

  3

• daddydrac/contextualbandits

  Python implementations of contextual bandits algorithms

  Language:Python2

• daddydrac/LiteratureDL4Graph

  2

• daddydrac/Contextual-Multi-Armed-Bandits

  Language:Jupyter Notebook349

• daddydrac/PySpark-Confluent-Kafka-Apache-Drill-

  A code-based tutorial for production level data streaming with PySpark plus Optimus for data cleaning, Confluent Kafka, & Apache Drill using Docker and Cassandra (NoSQL DB) for storage; This allows for for fast feature engineering and data cleaning.

  Language:Jupyter Notebook2611

• daddydrac/bandit-box

  BanditBox: A reproducible and portable GPU and TPU (TensorRT) accelerated machine learning container for advanced applications such as NLP, contextual bandits, policy gradient networks, & Deep Q Learning.

  Language:Jupyter Notebook112

• daddydrac/-Subscription-Customer-or-Regular-Customer

  Machine Learning to determine if the customer will be a monthly subscription customer (Like Dollar Shave Club, Spotify, Pandora or a Amazon Prime Member), or will they just remain a regular/free customer?

  Language:Jupyter Notebook33

• daddydrac/customer-lifetime-value-contractual-or-non-contractual-relationship

  Machine Learning to determine Customer Lifetime Value in a contractual or non-contractual setting.

  Language:Jupyter Notebook84

• daddydrac/Machine-Learning-for-Industrial-IoT-Applications

  Machine Learning for Industrial IoT Applications: Predict how long a part will work before performance degrades Perect for 5G cell phone towers, mining, aerospace, large/heavy equipment, farming, autonomous vehicles and even data centers.

  Language:Jupyter Notebook3510

• daddydrac/machine-learning-predict-customers-next-purchase

  Machine Learning to predict a customer's next purchase - Fulfills many use-cases from recommendation systems to loyalty programs.

  Language:Jupyter Notebook119

• daddydrac/Machine-Learning-to-Predict-Customer-Loyalty-Trajectory

  Customer loyalty is the strength of the relationship a customer has with a business as manifested by customer purchasing more and at high frequency. There are various signal or events related to a customer’s engagement with a business. Some examples are transactions, customer service calls and social media comments.

  Language:Python107

• daddydrac/Anaconda-CUDA-Accelerated-TensorFlowGPU-Development-Environment

  A reproducible containerized environment with CUDA X, Anaconda, TensorFlow-GPU, Keras-GPU, Dask, and PyCUDA.

  Language:Python244

• daddydrac/ubuntu

  Ubuntu Dockerfile for trusted automated Docker builds.

  2

• daddydrac/Computer-Vision-Facial-Key-Point-Detection

  Facial Key Point Detection Using HAAR Cascades on a trained Convolutional Neural Network

  Language:Jupyter Notebook73

• daddydrac/Algorithmic-Data-Cleaning-with-Pandas

  Algorithmic accumulator that walks arrays right (reduceRight) while handling conditions without mutations to variables, no loops, and zero non deterministic code design patterns.

  Language:Python8

• daddydrac/NVIDIA-Rapids-NeMo-PyTorch-Tensorboard

  Ultimate NLP Toolkit for GPUs: RAPIDS-AI, PyTorch, NeMo, Tensorboard, TensorRT, CUDA 10.1

  Language:Python102

• daddydrac/computer-vision-container

  This container is no longer supported, and has been deprecated in favor of: https://github.com/joehoeller/NVIDIA-GPU-Tensor-Core-Accelerator-PyTorch-OpenCV

  Language:Jupyter Notebook4417

• daddydrac/nginx-server-neo4j-graph-db

  NGINX server for NEO4J Graph Database and NEO4J REST API

  143

• daddydrac/Machine-Learning-For-Predictive-Lead-Scoring

  Predictive Lead Scoring does all the hard work for you by leveraging Machine Learning to provide your sales and marketing team with in-depth customer knowledge and ways to target the hottest and most qualified leads – resulting in saved time and higher revenue streams.

  Language:Jupyter Notebook9135

• daddydrac/physician-burnout-prediction

  3

• daddydrac/helm-chart

  2