Why Winners Keep Winning – Of Dollars And Data
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explained.ai
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The 50 Best Free Datasets for Machine Learning - Gengo AI
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Temporal Difference Learning in Python
So here I am after a quite long delay with another post. A lot happened during that time as I came back from our half-year South East Asia journey. I resumed my…
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NeuralCoref: Coreference Resolution in spaCy with Neural Networks.
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Bloom's 2 Sigma Problem - Wikipedia
Bloom's 2 sigma problem refers to an educational phenomenon observed by educational psychologist Benjamin Bloom and initially reported in 1984 in the journal…
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Iterative Model Design
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Code
# Copyright 2017 The Sonnet Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except…
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A Friendly Introduction to Cross-Entropy Loss
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[1806.01780] Mix&Match - Agent Curricula for Reinforcement Learning
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Selecting Subsets of Data in Pandas: Part 3
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[1806.01261] Relational inductive biases, deep learning, and graph networks
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[1502.04585] The Ladder: A Reliable Leaderboard for Machine Learning Competitions
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Improving Deep Learning Performance with AutoAugment
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Bootstrapping Your Way Through a Non-Random SEO Test
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Should we change our deed from tenants in commo - Q&A - Avvo
Lawyer directory Bankruptcy & Debt Bankruptcy & Debt Debt collection Debt settlement Credit repair lawyers Chapter 13 bankruptcy Chapter 11 bankruptcy Chapter 7…
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So Your Startup Received the Nightmare GDPR Letter · Jacques Mattheij
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How to easily do Topic Modeling with LSA, PSLA, LDA & lda2Vec
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Understanding Instrumental Variables
Suppose, as many do, that we want to estimate the effect of an action (or treatment) on an outcome. As an example, we might be interested in estimating the…
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Introducing Machine Learning Practica
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4.1. Pipelines and composite estimators — scikit-learn 0.20.dev0 documentation
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Invisible asymptotes
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Fast animal pose estimation using deep neural networks
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Artificial Intelligence — The Revolution Hasn’t Happened Yet
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ML beyond Curve Fitting: An Intro to Causal Inference and do-Calculus
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The 9.9 Percent Is the New American Aristocracy
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fast.ai NLP · Practical NLP
Introducing state of the art text classification with universal language models Written: 15 May 2018 by Jeremy Howard and Sebastian Ruder • Classification This…
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Elitist shuffle for recommendation systems In today's high pace user experience it is expected that new recommended items appear every time the user opens the…
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Can poor models be used in control loops and still achieve near-optimal performance? In recent posts, we’ve seen the answer is certainly “maybe.” Nominal…
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Announcing glom: Restructured Data for Python — Sedimental
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Deep Learning 2: Part 2 Lesson 8 – Hiromi Suenaga – Medium
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With Great Power Comes Poor Latent Codes: Representation Learning in VAEs (Pt. 2)
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[1805.01070] What you can cram into a single vector: Probing sentence embeddings for linguistic properties
[1805.01070] What you can cram into a single vector: Probing sentence embeddings for linguistic properties Cornell University Library We gratefully acknowledge…
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Program Synthesis Papers at ICLR 2018 – Illia Polosukhin – Medium
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Facebook AI | Tools | Open Source Deep Learning Tools
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TDM: From Model-Free to Model-Based Deep Reinforcement Learning
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COMS W4995 Applied Machine Learning Spring 2018 - Schedule
Press P on slides for presenter notes. Wk Date Topic Reading Comments 101/17/18 Introduction IMLP Ch 1, APM Ch 1-2 201/22/18 Software infrastructure IMLP Ch 1,…
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28 November 2017 by Richard Abstract : If you are still using a Gibbs sampler, you are working too hard for too little result. Newer, better algorithms trade…
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