A Collection of Conference & School Notes in Machine Learning

In this repo I collect my visual conference & summer school sketch notes - to prevent things getting messy. Feel free to have a look and enjoy, @RobertTLange!

FAQs

Q: What tablet do you use? A: I use an iPad 12.9' with the new Apple Pencil. But you don't have to. There are many cheaper tablet which do the job and I have seen awesome handwritten notes.
Q: What apps do you use? A: I use notability for all the talk sketches and procreate for illustrations. But I have also heard many good things about GoodNotes. Have a look at my recent blogpost in which I discuss my personal Machine Learning Research-iPad setup.
Q: Any advice on how to take notes? A: Ask yourself what type of notes you are would like to come back to in a week, month, or year. Also have a look at Natalia Vélez. Her sketches are awesome! And practice on talks by great speakers. A well structured talk is way easier to summarise.
Q: Is there a gallery of all your notes? A: Yes, there is! Check out the Web UI visual-ml-notes.

Finally, I also put together a couple of slides describing my favorite aspects and journey of collecting the notes 🤗

Previously Sketched Events

Date	Name	Type	Location	Notes	Program
20-12	NeurIPS	Conference	Virtual	Click	Click
20-07	MLSS	Summer School	Virtual	Click	Click
20-04	ICLR	Conference	Virtual	Click	Click
19-12	NeurIPS	Conference	Vancouver (Canada)	Click	Click
19-09	Bernstein	Conference	Berlin (Germany)	Click	Click
19-09	CCN	Conference	Berlin (Germany)	Click	Click
19-08	BMS	Summer School	Berlin (Germany)	Click	Click
19-07	EEML	Summer School	Bucharest (Romania)	Click	Click
19-06	RAAI	Conference	Bucharest (Romania)	Click	Click
19-06	FENS ENCODS	PhD Symposium	London (UK)	Click	Click
18-12	NeuRIPS	Conference	Montreal (Canada)	Click	Click
18-07	FENS Forum	Conference	Berlin (Germany)	Click	Click
17-08	ESSIR	Summer School	Barcelona (Spain)	Click	Click
17-08	DS^3	Summer School	Paris (France)	Click	Click

A Collection of Conference & School Notes in Machine Learning 🦄📝🎉

Related tags

Overview

A Collection of Conference & School Notes in Machine Learning

FAQs

Previously Sketched Events

Owner

Decision tree is the most powerful and popular tool for classification and prediction

Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku

This is my implementation on the K-nearest neighbors algorithm from scratch using Python

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning

A linear equation solver using gaussian elimination. Implemented for fun and learning/teaching.

Implementation of K-Nearest Neighbors Algorithm Using PySpark

Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.

Napari sklearn decomposition

[DEPRECATED] Tensorflow wrapper for DataFrames on Apache Spark

To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.

Getting Profit and Loss Make Easy From Binance

CS 7301: Spring 2021 Course on Advanced Topics in Optimization in Machine Learning

Gaussian Process Optimization using GPy

It is a forest of random projection trees

Random Forest Classification for Neural Subtypes

Tribuo - A Java machine learning library

Avocado hass time series vs predict price

ArviZ is a Python package for exploratory analysis of Bayesian models

A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo