Pinned Repositories
002_MachineLearning_eBook
Advanced-machine-learning
AIT_Trading_Algorithms
Alpha Factors and Trading Algorithms on Quantopian created by Philip Kiely, Richard Greenbaum, Rudolph Hernandez, and Alex Foster for our Data Mining final project.
awesome-algorithmic-trading
A curated list of awesome algorithmic trading frameworks, libraries, software and resources
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
EliteQuant_Python
Python quantitative trading and investment platform; Python3 based multi-threading, concurrent high-frequency trading platform that provides consistent backtest and live trading solutions. It follows modern design patterns such as event-driven, server/client architect, and loosely-coupled robust distributed system. It follows the same structure and performance metrix as other EliteQuant product line, which makes it easier to share with traders using other languages.
gnidart
Reference for Financial Trading
Machine-Learning-and-Reinforcement-Learning-in-Finance
Machine Learning and Reinforcement Learning in Finance New York University Tandon School of Engineering
Quantum-Machine-Learning
Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web [krishnakumarsekar/awesome-quantum-machine-learning]
Quick-Ref-Cheat-Sheets
Quick-Ref-Cheat-Sheets
uhasan1's Repositories
uhasan1/EliteQuant_Excel
EliteQuant Excel for Quantitative Modeling, Trading, and Portfolio Management. It enables you to create quantitative financial models in Excel spreadsheet, in the same way how financial professionals such as traders, quants, and portfolio managers do their day to day work. You are able to create pricing tools for products across all asset classes such as interest rate or FX, and from plain vanilla to exotic instruments. You are also able to backtest and live trade from Excel, with the so-called RTD, or real-time data support.
uhasan1/deeplearning.ai-Assignments
uhasan1/DeepLearningStars
Top Deep Learning Projects based on their Stars!
uhasan1/Deep-Neural-Network-Implementation
uhasan1/algorithm-essentials
算法精粹--举一反三，抛弃题海战术
uhasan1/Data-Science-Machine-Learning-Cheat-Sheet
Data Science Cheat Sheet is help to remind code with in minute and also useful to recall the code.Collecting at one place so everyone can access easily and learn.In this we have collected all cheat sheet from the web which is contain basic learning for python and R with Machine Learning and Data Science.
uhasan1/Predicting-Health-Insurance-Cost
Predicting health insurance cost from Morality data using Machine Learning techniques
uhasan1/VIX_MODEL
using one-day options with all strike price to calculated VIX value by using "“More than you ever wanted to know about volatility swaps” by Kresimir Demeterfi, Emanuel Derman, Michael Kamal and Joseph Zou, Goldman Sachs Quantitative Strategies Research Notes, March 1999. " approach
uhasan1/stat-nlp-book
Interactive Lecture Notes, Slides and Exercises for Statistical NLP
uhasan1/gpss17
Gaussian Process and Uncertainty Quantification Summer School 2017
uhasan1/auquan-toolbox-python
Backtesting toolbox for trading strategies
uhasan1/machine-learning-notes
Jupyter notebooks for Machine Learning practice
uhasan1/baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
uhasan1/python-constraint
Constraint Solving Problem resolver for Python
uhasan1/VOL_PCA_analysis
uhasan1/rl_algorithms
I am implementing a lot of reinforcement learning and imitation learning algorithms since I'm sick of reading about them but not really understanding them.
uhasan1/facets
Visualizations for machine learning datasets
uhasan1/Bayesian-Deep-Learning-Papers
Alpha-I's curated list of Bayesian Deep Learning papers
uhasan1/edward
A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.
uhasan1/BlackStone-Entities
Analysis of firms datasets from online resources for potential blackstone company entities. -- scraping -- sec pull -- edgar
uhasan1/neural-network-papers
uhasan1/SuccessfulAlgorithmicTrading
Successful Algorithmic Trading by Michael L. Halls-Moore
uhasan1/criteo-1tb-benchmark
Benchmark of different ML algorithms on Criteo 1TB dataset
uhasan1/Research
uhasan1/minibook-2nd-code
Code of the IPython Minibook, 2nd edition (2015)
uhasan1/Algorithmic-Trading-Challenge---Kaggle
Algorithmic Trading Challenge implemented as part of the term project for Foundations of Machine Learning at NYU Courant in Fall 2016 (http://cs.nyu.edu/courses/fall16/CSCI-GA.2566-001/index.html/)
uhasan1/TF-Tutorials
A collection of deep learning tutorials using Tensorflow and Python
uhasan1/booknotes
Notes I'm taking when reading books
uhasan1/coding_practice
uhasan1/Goldman-Sachs_contest_Bond-Liquidity-Prediction
Predict the Liquidity of Bond.