Data Science vs Data Engineering



Is this still relevan?

#datascience #dataengineering

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One of the BEST #MachineLearning Glossary by Google


It will definitely come in handy - https://lnkd.in/gNiE9JT


#machinelearing #glossaries #patternrecognition #artificialintellegence

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#NLP is among the hottest and most interesting fields in #datascience. Check out these 5 in-depth and hands-on tutorials to learn #NLP:

1. The Essential NLP Guide to Solve Top 10 Common NLP Tasks - https://lnkd.in/fiXS5Rj
2. Practical Tutorial for Regular Expressions in #Python - https://lnkd.in/fXw-Rdz
3. A Gentle Introduction to #TopicModeling - https://lnkd.in/fDXmt4n
4. Comprehensive and Intuitive Guide to #WordEmbeddings - https://lnkd.in/fvRrFhA
5. #TextClassification using #ULMFiT and #fastai Library in Python - https://lnkd.in/f7bu8jM

And test your #NaturalLanguageProcessing knowledge on this challenging question set!
30 Questions to test a data scientist on Natural Language Processing - https://lnkd.in/fpWBZUh

✴️ @AI_Python_EN

#ReinforcementLearning is making waves - now is as good a time as any to learn what it's about. Check out these 4 articles to get started:

1. Simple Beginner’s guide to Reinforcement Learning & its implementation - https://bit.ly/2tUOPhB
2. Reinforcement Learning Guide: Solving the Multi-Armed Bandit Problem from Scratch in #Python - https://bit.ly/2NSC1kN
3. Introduction to Monte Carlo Learning using the OpenAI Gym Toolkit - https://bit.ly/2VOddx1
4. Nuts & Bolts of Reinforcement Learning: Model Based Planning using Dynamic Programming - https://bit.ly/2NOV6UY

✴️ @AI_Python_EN

How neural networks learn' - Part III: The learning dynamics behind generalization and overfitting:


https://www.youtube.com/watch?v=pFWiauHOFpY

#neuralnetwork

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Variational Autoencoders Pursue PCA Directions (by Accident)

Rolinek et al.: https://lnkd.in/efNRnb9

#ArtificialIntelligence #DeepLearning #MachineLearning #ComputerVision #PatternRecognition

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AI Safety Needs Social Scientists

Irving et al.: https://lnkd.in/exUPmFy

#AIEthics #AIGovernance #ArtificialIntelligence

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Comparison of hot jobs of global #datascience analytics industry: Data Scientist vs Data Engineer vs Statistician. Download the infographic and decide the best job role for you!
https://bit.ly/2CegSgn

✴️ @AI_Python_EN

There's an art to running ML models in production the right way - and that's where a fluid DataOps plan becomes even more useful #DataScience #ODSC BluevineCapital https://hubs.ly/H0gQGkw0

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Hacking Google reCAPTCHA v3 using Reinforcement Learning

Paper: https://lnkd.in/es9AjzC

#reinforcementlearning #research #ai #artificialintelligence #machinelearning

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Google launches TensorFlow Lite 1.0 for mobile and embedded devices

https://venturebeat.com/2019/03/06/google-launches-tensorflow-lite-1-0-for-mobile-and-embeddable-devices/

#tensorflow #machinglearning #ai for #mobiledevices

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Towards Structured Evaluation of Deep Neural Network Supervisors

Paper: https://lnkd.in/evfuQAq

#neuralnetworks #ai #machinelearning #artificialintelligence #deeplearning #research

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neuralRank: Searching and ranking ANN-based model repositories

Paper: https://lnkd.in/edxKPBH
#artificialinteligence #research #machineleaning #neuralnetworks

✴️ @AI_Python_EN

So mesmerizing 😵! Python code to submit rotated images to the Cloud Vision API + R code for visualizing it. This repository was used to create this animation. Quite amazing to see what the neural network aka Google's Cloud Vision API is seeing where we or at least I needed some time to see that there is a rabbit 🐇 in the duck 🦆 or vice versa. Credits to Max Woolf for the animation. He also open-sourced the code to generate this animation. #deeplearning #machinelearning

Github: https://lnkd.in/dJ9V6tC

✴️ @AI_Python_EN

How can AI become biased? 2 papers investigate:

Joy Buolamwini et al show that AI has a higher error rate when recognizing darker-skinned female faces: http://bit.ly/2C2pxT9

IBM responds to their paper, explaining how they reduced that error: http://bit.ly/2C82u9n #TechRec #ArtificialIntelligence

✴️ @AI_Python_EN

OpenAI has created activation atlases (in collaboration with Google researchers), a new technique for visualizing what interactions between neurons can represent.

As AI systems are deployed in increasingly sensitive contexts, having a better understanding of their internal decision-making processes will let us identify weaknesses and investigate failures.

Blog: https://lnkd.in/d4i6xQC
Paper: https://lnkd.in/dGNcd4K
Github: https://lnkd.in/d-2WhfN
Demo: https://lnkd.in/dBiHZv3

#deeplearning #research

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New NLP News: GPT-2, Sequence generation in arbitrary order, and much more http://newsletter.ruder.io/archive/160799

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Deep Learning for Science School

July 15 - 19th, 2019

Lawrence Berkeley National Laboratory, Berkeley, CA

Hosted by Computing Sciences at Berkeley Lab: https://dl4sci-school.lbl.gov/

#artificialintelligence #deeplearning #sciences

✴️ @AI_Python_EN

Full-stack data science and engineering will prevent innovation

Regardless of the size of your organisation, if you want to use data science to innovate for your industrial output, don't push for a full-stack data scientist. Prevention of specialising will kill innovations. Data science means R&D work at the core and data and ML engineering requires a different focus. The collaboration of course needed but one-fit-all is a doomed strategy for innovation.

#datascience #ml #datascienceisresearch

✴️ @AI_Python_EN

Real-Time AR Self-Expression with Machine Learning #DataScience #MachineLearning #ArtificialInteligence http://bit.ly/2tYa7Lh

✴️ @AI_Python_EN

This part only provides a quick glance at some important features in Python 3. If you're interested in all of the most important features, please read the official document, What’s New in #Python .

Github Link - https://lnkd.in/ftcp5jQ

#python #datascience #machinelearning #dataanalysis

✴️ @AI_Python_EN