kbmajeed Goto Github PK
Name: kbmajeed
Type: User
Bio: Machine Learning, Data Science, Deep Learning, Robotics, Computer Vision, Control Theory.
Twitter: kbmajeed
Location: Atlanta, GA, USA
kbmajeed's Projects
msds621
Course notes for MSDS621 at Univ of San Francisco, introduction to machine learning
nd0821-c2-build-model-workflow-exercises
Exercise Code for Course 2 of the Udacity ML DevOps Nanodegree Program
nigeria_covid19
Repository on the COVID-19 Cases in Nigeria
numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
nvidia_gtc2020
online_learning_challengesng
optimtraj
A trajectory optimization library for Matlab
panoramas
particle
A simple portfolio Jekyll theme:
particle_filter_tracking
particleswarmoptimization
Matlab implementation of particle swarm optimization. Well documented with examples.
pdf_cv
pdf_cv
pi_numba
portfolio_simulator
practical-deep-learning-book
Official code repo for the O'Reilly Book - Practical Deep Learning for Cloud, Mobile & Edge
practical_rl
A course in reinforcement learning in the wild
prml
PRML algorithms implemented 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 ;)
prohack-solution---d1d-team
Our solution to the data science hackathon by McKinsey, Prohack by our team D1D, which was ranked 4th on public leaderboard and 25th on private leaderboard.
pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
pyqt_application
randomforest_trader
rcnn
R-CNN: Regions with Convolutional Neural Network Features
rhino_tracking
rnn_dinosaurs
rnn_yoruba_names
rpg_quadrotor_control
Quadrotor control framework developed by the Robotics and Perception Group
safeopt
Safe Bayesian Optimization
scut-fbp5500-database-release
A diverse benchmark database for multi-paradigm facial beauty prediction
sealionvision
A CV model is developed to extract samples and trained using CNN to classify Sea lions from aerial images into classes: adult males, sub adult males, adult females, juveniles and pup respectively.
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