nmarwen's repositories
1on1-questions
Mega list of 1 on 1 meeting questions compiled from a variety to sources
algorithmic-examples
Algorithmic Marketing Models
auto-py-to-exe
Converts .py to .exe using a simple graphical interface
blog
Source code and other material for my blog posts.
cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
forecasting
Time Series Forecasting Best Practices & Examples
HandsOn-Unsupervised-Learning-with-Python
HandsOn-Unsupervised-Learning-with-Python, Published by Packt
hello_tf_c_api
Neural Network TensorFlow C API.
homemade-machine-learning
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Introduction-to-Time-Series-forecasting-Python
Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.
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.
machine_learning_refined
Notes, examples, and Python demos for the textbook "Machine Learning Refined" (Cambridge University Press).
MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
ML-DL-in-production
Repository, with some blogposts and code for deploying machine and deep learning-based models in production.
ml-projects
ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
python_for_scientists
Python Open Courseware for Scientists and Engineers
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
scipy_con_2019
Tutorial Sessions for SciPy Con 2019
scope_guard
Scope Guard & Defer C++
semver
Semantic Versioning C++
state_saver
State Saver C++
statrethinking_winter2019
Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
stockpredictionai
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.
timeseries_demo
A short introduction to time series methods