karpathy

"""
A bare bones examples of optimizing a black-box function (f) using
Natural Evolution Strategies (NES), where the parameter distribution is a 
gaussian of fixed standard deviation.
"""

import numpy as np
np.random.seed(0)

# the function we want to optimize

Kaixhin

I supervise undergraduate/postgraduate/UROP projects as part of BICV. The PI, Dr Anil Bharath, has a nice set of FAQs for prospective research students, which should give you an idea of what our group specialises in. My topic of research is deep reinforcement learning, which is less focused on computer vision and more on general machine learning or even artificial intelligence. Note that I only supervise students at Imperial College London, so please do not contact me about supervision otherwise.

I expect students to be a) highly motivated and b) technically proficient.

a) Projects that I supervise revolve around cutting-edge research, and specifically deep learning. Projects can, and have in the past, relied on research released during the course of the project. Some parts of machine learning can be found in optional modules in bioengineering courses, but (modern) deep learning is currently not taught at Imperial (as far as I am aware). I usually give crash

bsweger

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

henrik

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name: