Data Machina

By alg01

Data Machina - Issue #132

#132・ Jun 10, 2018

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Data Machina - Issue #132

By alg01 • Issue #132 • View online

Crucially, there’s a renaissance of tools for visualizing large-scale, high-dimensional data. Uber just open sourced Kepler - an awesome geospatial analysis tool for large-scale datasets. Days ago, Google open sourced a Tensorflow.js library for real-time interactive tSNE visualization of large, high-dimensional datasets in the browser. And my Dutch geek friends tell me this has just been released: Vaex- Lazy Out-of-Core Python DataFrames for visualizing big tabular data at a billion rows per second in your laptop. Amazing tools!

Sorry as I *really* didn’t intend to skip last week. It took a toll on me travelling to project sites in Frankfurt and Leeds, where I tried to convince certain old guard oh! Enterprise Architects about the wonders of the Lambda Architecture for real-time, large-scale machine learning.

While enduring planes & trains back to London, I really enjoyed reading The Incredible Machine

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10 Link-o-Troned

1. [new] MLflow: An Open Source Machine Learning Platform

2. Torus: A Toolkit For Docker-First Data Science

3. How a Kalman Filter Works, In Pictures

4. The Building Blocks of Neural Networks Interpretability

5. The 7 Pillars of Causal Reasoning with Reflections on ML (pdf)

6. Probabilistic Predictions: Friendly Intro to Cross-Entropy Loss

7. An Open Source Tool for Auditing Machine Learning Models

8. So Your Data Science Project Isn’t Working

9. [free MIT video course] The Human Brain

10. [free ebook] Data Science for Startups

A Pythonista *Experience*

1. FastAI PyTorch Serverless API with AWS Lambda

2. Fast, Flexible, Performant Feature Selection for Python

3. [free ebook] Python Code for AI (pdf, 221 pages)

Scripting aRt

1. Can We Predict Flu Outcome with Machine Learning in R?

2. [new] xplain: Interactive Interpretation of Statistical Results

3. Intro to Building Deep Neural Nets with Keras in R

Love from Julia

1. Automatic Differentiation in 10 minutes with Julia

2. EAGO - Easy, Advanced Global Optimization in Julia

3. PredictMD - A Uniform Interface for Machine Learning in Julia

(Paren(th)ethical)

1. The Feynman Machine - AI Architecture in Clojure

2. Deodorant: Solving the Problems of Bayesian Optimization

3. Hyperfiddle - Interactive Prototyping with Datomic Databases

ScalaTOR

1. Numerical (Matlab-like) and Symbolic (Mathematica-like) Tool

2. A Scala ETL Library for Machine Learning Data Pipelines

3. Easy, Large-scale, Distributed Graph Processing in Scala

data v-i-s-i-o-n-s

1. Quickly Build Horizon Charts for Time-series in D3

2. A Tidy Workflow for Visualizing Time-series Anomalies

3. All Roads Lead to Rome - Visualizing 3.3 Million Journeys

Distributed de-Entangler

1. Gimel: Paypal’s Distributed Analytics Processing Platform

2. Missing the Point About Microservices

3. Real Time Anomaly Prediction in Distributed Systems

Blockchain Über Alles

1. High-performance, Open Source Smart Contract Platform

2. The State of the Ethereum Network

3. Standford Uni - Predicting Price Changes in Ethereum (pdf)

IoTea - everyThing/anyThing

1. Run IoT Apps in Any Language on Multiple Linux ARM Devices

2. My Bathroom Mirror is Smarter than Yours

3. IoT Security & Pentesting 101 - A Reading List

Forschung!

1. GANs vs. Gaussian Mixture Models for High Dimensional Data

2. Scalable Multi-Class Bayesian Support Vector Machines

3. New Machine Intelligence Framework: Concepts & Prototype

Algorithmic Potpourri

1. An Algorithm for Compressing Space and Time

2. Probabilistic Algos for Approximate Matrix Decomposition

3. Distributed Algorithms: An Intuitive Approach (pdf, 392 pages)

Robots & Cyborgs like <you>

1. Teaching My Robot with Tensorflow

2. Living with a Mind-controlled Robotic Arm

3. A Curated List of Awesome Robotics Libraries

Deep Learning Bits

1. Common Architectures in Convolutional Neural Networks

2. Distributed Deep Training for TensorFlow, Keras & PyTorch

3. Deep Learning Notebooks - The Straight Dope with MXNet

startups -> radar

1. JustML- Automatic Machine Learning for Data Scientists

2. Weight & Biases- Performace Dataviz for ML at Scale

3. Pozus - AI for Fast & Accurate Human Pose Estimation

ML Datasets & Stuff

1. UC Berkeley Open-Source 100k Driving Video Database

2. The Liver Tumour Dataset Segmentation Challenge

3. Explore the Largest Electricity & Carbon Dataset

Postscript, etc

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Tips? Suggestions? Feedback? Send email to Carlos

Curated by Carlos @ds_ldn in the middle of the night.

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alg01

By alg01

A weekly digest of machine learning curiosities, data science geekery, and other data amenities.

Curated by @ds_ldn in the middle of the night.

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