Mohamed Abuella's Projects
CyMySQL: Python MySQL Client powered by Cython
Dive into Deep Learning, Berkeley STAT 157 (Spring 2019) textbook. With code, math, and discussions.
Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
A python library for easy manipulation and forecasting of time series.
Data Analysis Using Python
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
This projects adopts machine learning models to quantify the daily/hourly bunker fuel consumption of a ship in different sailing speed, displacement/draft, trim, weather, and sea conditions. The industry data utilized include voyage report data, sensor data, AIS data, and meteorological data. Apart from Python code, here, we also share 130 trained machine learning models that enable you to estimate the daily/hourly fuel consumption of eight 8100-TEU to 14,000-TEU containerships. To download our trained machine learning mdoels and use them for estimate/forecost ship fuel consumption rate (ton/day, ton/hour), read "Instructions on How to Use Trained Machine Learning Models". For our Python code, read "Readme - Organization of Python Code Files in This Project".
The Data Exploration lesson in the Reproducible Science using Jupyter Notebooks curriculum
Collection of useful data science topics along with code and articles
Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques
code for Data Science From Scratch book
Self-study plan to achieve mastery in data science
Collection of data science projects in Python
A collection of data science resources worth bookmarking
R's data.table package extends data.frame:
SVM classification and regression for some QSAR modelling.
R package to create interactive courses for www.datacamp.com
Code repository supporting the medium blog
Open Source Data Science Resources.
Course notes for Andrew Ng's new deep learning specialization on coursera
The code of the paper 'Deep Forecast : Deep Learning-based Spatio-Temporal Forecasting", ICML Time Series Workshop 2017.
Projects include the application of transfer learning to build a convolutional neural network (CNN) that identifies the artist of a painting, the building of predictive models for Bitcoin price data using Long Short-Term Memory recurrent neural networks (LSTMs) and a tutorial explaining how to build two types of neural network using as input the MNIST dataset, namely, a CNN using Keras and a fully-connected network using TensorFlow.
Repository for series of Medium Articles introducing Deep Learning for NLP.
SuperComputing 2017 Deep Learning Tutorial
ML_tutorials
Code repository for Deep Learning with Keras published by Packt
Jupyter notebooks for the code samples of the book "Deep Learning with Python"