Name: Amir Nejad , PhD.
Type: User
Bio: A Data Scientist and Petroleum Engineer. Interested in variety of topics such as machine learning, statistical methods, time series analysis and big data.
Twitter: Dr_Nejad
Location: Houston, Texas, USA
Blog: https://www.linkedin.com/in/amir-nejad-phd-8690a44b
Amir Nejad , PhD.'s Projects
Coursera Peer Reviewed Assignment
A collection of algorithms and data structures
A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading.
How to do Bayesian statistical modelling using numpy and PyMC3
Characterizing possible failure modes in physics-informed neural networks.
repo for series of articles on medium regarding convolutional neural network evoloution
A Code-First Introduction to NLP course
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
Code from the "CUDA Crash Course" YouTube series by CoffeeBeforeArch
moDel Agnostic Language for Exploration and eXplanation
In the series of Python notebooks I am going to practice solving questions with common data science and machine learning techniques and I am going to share the notebooks here.
The Leek group guide to data sharing
:globe_with_meridians: Deep Embedded Self-Organizing Map: Joint Representation Learning and Self-Organization
Various implementations of GAN using Pytorch
Python scripts that use the Interactive Brokers TWS API
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
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.
Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.
A collection of machine learning examples and tutorials.
Mapping Houston Real Estate Price Data with Python and Basemap
Repository containing notebooks of my posts on Medium
Machine Learning Engineering Open Book
My codes and notes on Natural Language Processing Specialization class from coursera
Natural Language Processing Best Practices & Examples
NLTK Source