Data Science Engineering
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Machine Learning, Data Science, Engineering, Programming.
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Forwarded from Programming Resources via @like
Papers With Code highlights trending ML research and the code to implement it.
تو این سایت کسایی رو که مقاله دادن و پیاده سازی‌هاشون رو در اختیار عموم قرار دادن لیست کرده (به همراه خود مقاله و کد پیاده‌سازی شده)

#paper #neural_network #state_of_the_art #machine_learning
thanks to: @aznourian
@pythony

https://paperswithcode.com
Forwarded from Data Science Boom
Using AI to help increase blood donations
http://bit.ly/2HT082O

Turing Award Won by 3 Pioneers in Artificial Intelligence
https://nyti.ms/2HU0mGJ

Common statistical tests are linear models (or: how to teach stats)
http://bit.ly/2WBtDt7

Towards Robust and Verified AI: Specification Testing, Robust Training, and Formal Verification
http://bit.ly/2WytczM

Strategies for working with new data
http://bit.ly/2HU0KoF
​​Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening

Paper claims model to perform better than human.

ArXiV: https://arxiv.org/abs/1903.08297
GitHub (code & models): https://github.com/nyukat/breast_cancer_classifier

#BreastCaner #healthcare #DL #CV
​​🔥DeepMind released dataset for training algebraic perception

Mathematics Dataset is a large-scale extendable dataset of mathematical questions, for training (and evaluating the abilities of) neural models that can solve algebraic problems (reason algebraically).

ArXiV: https://arxiv.org/abs/1904.01557
GitHub: https://github.com/deepmind/mathematics_dataset
Forwarded from Data Science Boom
AI disaster won’t look like the Terminator. It’ll be creepier.
http://bit.ly/2WNjR7c

Asking the Right Questions with Machine Learning
http://bit.ly/2G3ax9V

Artificial Intelligence in Healthcare – A Comprehensive Overview
http://bit.ly/2G01F4W

Nuts and Bolts of Reinforcement Learning: Introduction to Temporal Difference (TD) Learning
http://bit.ly/2WMPaPS

DeepMind and Google: the battle to control artificial intelligence
http://bit.ly/2WPBJP9
Forwarded from Data Science Boom
Boom! What to read on the weekend, Issue #57

16 OpenCV Functions to Start your Computer Vision journey (with Python code)
http://bit.ly/2WQLf4C

Top 15 Data Science Podcasts Worth Listening To
http://bit.ly/2I19tFU

R vs Python for Data Visualization
http://bit.ly/2I1AA3u

Two new planets discovered using artificial intelligence
http://bit.ly/2WMend1

Reinforcement Learning vs. Differentiable Programming
http://bit.ly/2WIEEsG

Artificial intelligence: the art world’s weird and wonderful new medium
http://bit.ly/2I2HzcB

For Data Warehouse Performance, One Big Table or Star Schema?
http://bit.ly/2WNxinJ

How to Discover the AI Initiatives of Fortune 500 Companies
http://bit.ly/2I2SQcS

Why Differential Privacy Should Be Top of Mind for Data Science and Governance Teams
http://bit.ly/2WNxkMn

AI Learning Accelerator by ODSC
http://bit.ly/2WPWMkC
Make Trump Sing Again

Generated by a Trump TTS model trained based off the paper "Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis", where given a reference audio the model will try to replicate that style.

ArXiV: https://arxiv.org/pdf/1803.09017.pdf
Youtube: https://youtu.be/3rgAVT8b4fw

#tts #song #speech #DL
Forwarded from Data Science Boom
The Data Science Career Guide
http://bit.ly/2I5ew8d

19 Data and Analytics Predictions Through 2025
http://bit.ly/2WS5te4

Common Data Mistakes to Avoid
http://bit.ly/2IaKL5U

spaCy Cheat Sheet: Advanced NLP in Python
http://bit.ly/2WX2pgN

The Emotions Recognized in Vocal Bursts (interactive map)
http://bit.ly/2WOtBhM
Forwarded from Data Science Boom
Top 10 Coding Mistakes Made by Data Scientists
http://bit.ly/2WWLc77

What the car industry’s AI problem tells us about the future of work
http://bit.ly/2I8NzAr

"Data Scientist" is the hottest profession of 2019 according to job-listing data
http://bit.ly/2X121xY

800 scientists say it’s time to abandon “statistical significance”
http://bit.ly/2I8nJMZ

Putting data back into context
http://bit.ly/2X6xmzp
Computer Vision news from RSIP VISION. April 2019
Forwarded from EarthML
Automatic feature selection:

EGU is still ongoing, but I am burning to share with you some of my findings already!

Research group in University of Lausanne developed a pretty promising algorithm for automatic feature selection based on General Regression Neural Network (GRNN, also known as Nadaraya-Watson Estimator). The idea behind is pretty simple and therefor powerful - why won't we build the simplest network that can train really fast and brute force all possible combination of features to check how they affect accuracy, learning rate etc and than select the best performing once.

Here is Python implementation on GitHub: https://github.com/federhub/pyGRNN
Also, check their poster: https://github.com/federhub/pyGRNN/blob/master/EGU2019_FS_using_simple_and_efficient_ML_models.pdf

Stay tuned, subscribe and share!
xoxo
​​Autodesk claims to use GANs to design a chair.

First-of-its-kind chair from Philippe Starck and Kartell. Imagined by a human and cocreated with intelligent generative design

Link: https://adsknews.autodesk.com/news/starck-intelligent-generative-design
Generative design explanation link: https://www.autodesk.com/solutions/generative-design

#Autodesk #generativedesign
Forwarded from Data Science Boom
What does the future data scientist look like?
http://bit.ly/2IgHW3g

Explaining Random Forest (with Python Implementation)
http://bit.ly/2X2F6SI

The Growing Trend of Data Science in Japan
http://bit.ly/2WWRIee

Let's get LEGO'd! (in R)
http://bit.ly/2IdGaQw

Neural Machine Translation With Attention Mechanism
http://bit.ly/2IcvjpN
Forwarded from Data Science Boom
The first AI-generated textbook shows what robot writers are actually good at
http://bit.ly/2X8zp5O

Aroma: Using machine learning for code recommendation
http://bit.ly/2IkRzy1

doccano - open source text annotation tool for ML practitioner
http://bit.ly/2XdJFtp

Introducing d3-regression
http://bit.ly/2IihiqH

7 Qualities Your Big Data Visualization Tools Absolutely Must Have and 10 Tools That Have Them
http://bit.ly/2IlIEfv
Forwarded from Data Science Boom
The insideBIGDATA IMPACT 50 List for Q2 2019
http://bit.ly/2XdjRO2

Mathematicians Discover the Perfect Way to Multiply
http://bit.ly/2XaL8AM

dabl, the Data Analysis Baseline Library
http://bit.ly/2IkKvBs

Top 5 Interesting Applications of GANs for Every Machine Learning Enthusiast!
http://bit.ly/2XhEY25

A too complicated map
http://bit.ly/2Ikm9rt
Forwarded from Data Science Boom
The EU commission introduces guidelines for achieving a ‘Trustworthy AI’
http://bit.ly/2IhXILj

Best of arXiv.org for AI, Machine Learning, and Deep Learning – March 2019
http://bit.ly/2XbZjWe

Another all cheat-sheets in one place
http://bit.ly/2Il6eZO

Starting Your Career in Data Science: What Are Your Options?
http://bit.ly/2Ikrjn8

Fusing data and design to supercharge innovation—in products and processes
https://mck.co/2X58uI2
🔥Singing voice conversion system developed at FAIR-Tel Aviv.

This can transform someone's singing voice into someone else's voice.

YouTube: https://www.youtube.com/watch?v=IEpkGenLnjw
Link: https://venturebeat.com/2019/04/16/facebooks-ai-can-convert-one-singers-voice-into-another/
ArXiV: https://arxiv.org/abs/1904.06590

#voiceconversion #audiolearning #DL #Facebook
Forwarded from Data Science Boom
Boom! Weekly selection from DSB. Issue #50
The TOP 10 most popular links for the week

1. Here's who will die on 'Game of Thrones' according to AI
http://bit.ly/2IjaKIm

2. Another 10 Free Must-See Courses for Machine Learning and Data Science
http://bit.ly/2X5kTfc

3. The first AI-generated textbook shows what robot writers are actually good at
http://bit.ly/2X8zp5O

4. Mathematicians Discover the Perfect Way to Multiply
http://bit.ly/2XaL8AM

5. Google launches an end-to-end AI platform
https://tcrn.ch/2XeJnCR

6. Another all cheat-sheets in one place
http://bit.ly/2Il6eZO

7. Serverless for data scientists
http://bit.ly/2Ijg12B

8. A too complicated map
http://bit.ly/2Ikm9rt

9. How to Version Control Jupyter Notebooks
http://bit.ly/2XdWUL0

10. Best of arXiv.org for AI, Machine Learning, and Deep Learning – March 2019
http://bit.ly/2XbZjWe