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10-steps-to-become-a-data-scientist

📢 Ready to learn! you will learn 10 skills as data scientist:📚 Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.

accelerated_sampling_with_autoencoder

Accelerated sampling framework with autoencoder-based method

ase_ani

ANI-1 neural net potential with python interface (ASE)

autoarima-time-series-blog

This is the code notebook for the blog post on using Python and Auto ARIMA

barnaba

Analyse Nucleic Acids Structure and Simulations with baRNAba

barnaba_pseudotor

Addition of pseudotorsion caclulation eta, theta, eta', and theta' to barnaba package (https://github.com/srnas/barnaba)

begin-latex-in-minutes

📜 Brief Intro to LaTeX for beginners that helps you use LaTeX with ease.

colvars

Collective variables module for molecular simulation and analysis programs

complete-python-3-bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

data-science-books

datacamp

DataCamp data-science courses

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

encodermap

python library for dimensionality reduction

ff

Force Fields

ff-fitting-tools

force_fields

Force fields in various formats

gnina

A deep learning framework for molecular docking

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

lugano2019

Data for PLUMED tutorial in 2019 in Lugano

mdtoolbox

MDToolbox: A MATLAB/Octave toolbox for statistical analysis of molecular dynamics trajectories

metadynminer

Package for reading, analysis and visualization of metadynamics HILLS

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

mit_ocw_linear_algebra_18_06

IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)

mlreview_notebooks

Notebooks for "A high bias low-variance introduction to Machine Learning for physicists."

openmm

OpenMM is a toolkit for molecular simulation using high performance GPU code.

parmed

Parameter/topology editor and molecular simulator

plumed2-automatic-gradients

How to differentiate collective variables in free energy codes: Computer-algebra code generation and automatic differentiation

plumedautodiff-lugano-2019

Code accompanying my talk at "Open source software for enhanced-sampling simulations"

prodyna

versatile Protein Dynamics Analysis in R