Zack Seyun's repositories
Granular_Data_Analysis
Analyzing some datasets from Granular
Analyzing-the-Titanic-Dataset
Analyzing the Titanic Dataset by running some Machine Learning Models
awesome-project-ideas
Curated list of Machine Learning, NLP, Vision Project Ideas
BITCOIN-PRICE-PREDICTION-USING-SENTIMENT-ANALYSIS
Predicts real-time bitcoin price using twitter and reddit sentiment, and sends out notifications via SMS.
Block.One-BlockChain-Viewer
iOS Application to view the most recent blocks on the EOS Blockchain
blockchain
A simple Blockchain in Python
colabtools
Python libraries for Google Colaboratory
Data-Analysis
Data Analysis Using Python
kaggle-learning
Repository for sharing the knowledge from the learning path of Kaggle Learning. All contributions welcome :).
learning-apache-spark
This repository contains apache spark tutorials implemented with pypsark. For some machine learning methods, there will be comparisons between pyspark and R results.
Machine-Learning-Playground
Just a canvas for me to tweak some data through ML algorithms
Monster_com_Jobs_Dataset_Analysis
Exploring and Analyzing the data inside the Monster.com's Job datsets
neural_collaborative_filtering
Neural Collaborative Filtering
nmt-chatbot
NMT Chatbot
Plot.ly-Playground-Amazing-Visualizations
Repository for me to try a number of different interactive graphs and statistical visualizations
Public-Datasets
public datasets I can access in a cloud/server
Ripple_Explained
This is the code for "Ripple Explained" by Siraj Raval on Youtube
Sentiment-Analysis-Playground
Will attempt to use machine learning techniques to search for keywords on twitter and get the sentiment of whether a topic is positive,negative, or neutral
spark-scala-tutorial
A free tutorial for Apache Spark.
streamalert
StreamAlert is a serverless, realtime data analysis framework which empowers you to ingest, analyze, and alert on data from any environment, using datasources and alerting logic you define.
tflearn
Deep learning library featuring a higher-level API for TensorFlow.
ThinkStats2
Text and supporting code for Think Stats, 2nd Edition