hhtnghia321 Goto Github PK

advanced_programming_teaching

My teaching folder for Advanced Programming in DS & Finance 2019 at John von Neumann Institue

advm---svm-assignment---student-math-performance

ai-challenge-2020

assignment3

automobile-data-set---uci

autotrader

A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.

backing-marketing

bayesian-network

bootstrap-practice

challenge-lab

classical-music-generation---lstm

conditional-sig-wasserstein-gans

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

data-engineering-zoomcamp

Free Data Engineering course!

datasciencecoursera

datasharing

The Leek group guide to data sharing

dotfiles

some of my dotfiles

exdata_plotting1

Plotting Assignment 1 for Exploratory Data Analysis

exploratoryanalysis-week-4-peer-graded-assignment

fasttext-test

generative-models

research and implementations of Generative Models(GANs, VAEs and Autoregressive models) and their applications

hashtagcashtag

My Insight Data Engineering Fellowship project. I implemented a big data processing pipeline based on ​lambda architecture​, that aggregates Twitter and US stock market data for user sentiment analysis using open source tools - ​Apache Kafka ​for data ingestions, Apache Spark ​& ​Spark Streaming ​for batch & real-time processing, ​Apache Cassandra

homework-6---ml

income-major

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

mathematics-for-machine-learning-cousera

quizzes/assignments for mathematics for machine learning specialization on coursera

ml-chap3

ml-engineering

Machine Learning Engineering Guides and Tools

mlfinlab

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

mlmissingdatachap2