imran273 Goto Github PK

followers: 15.0 following: 1.0 repos: 279.0 gists: 0.0

Name: Muhammad Imran

Type: User

Company: Data Driven Asia

Bio: Indonesian, An Outstanding data analyst, 10 Year in Data analyst.

Location: Jakarta

Blog: https://www.linkedin.com/in/muhammad-imran-6791a514/

Muhammad Imran's Projects

sqoop2hive

Few scripts to automate daily data loads from RDBMS to Partitioned Avro Hive table

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

stockpredictions

Stock Predictions through NYTimes article headlines sentiment analysis.

stocks

Programs for stock prediction and evaluation

stocksight

Crowd-sourced stock analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis

streamingml

supervised-machine-learning

This repo contains regression and classification projects. Examples: development of predictive models for comments on social media websites; building classifiers to predict outcomes in sports competitions; churn analysis; prediction of clicks on online ads; analysis of the opioids crisis and an analysis of retail store expansion strategies using Lasso and Ridge regressions.

surreal

Open-Source Distributed Reinforcement Learning Framework by Stanford Vision and Learning Lab

swagger-ui

Swagger UI is a collection of HTML, Javascript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.

tacotron

A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model

targeted-marketing-predictive-engine

This project contains a banking dataset from UCI's website. I have created a predictive modeling engine using scikit-learn that will determine if a customer will avail to a Certificate of Deposit(CD) or not. Logistic Regression with Cross Validation training hyperparameters has been used for modeling and evaluation purposes.