AI, Python, Cognitive Neuroscience
3.88K subscribers
1.09K photos
47 videos
78 files
893 links
Download Telegram
Research Guide: Advanced Loss Functions for Machine Learning Models

http://bit.ly/36HBefu

#DataScience #MachineLearning #ArtificialIntelligence

❇️ @AI_Python_EN
Intro to optimization in deep learning: Momentum, RMSProp and Adam

https://bit.ly/2zwBLV0

❇️ @AI_Python_EN
A list of the biggest machine learning datasets from across the web

https://bit.ly/2TYGdVD

❇️ @AI_Python_EN
Self-training with Noisy Student improves ImageNet classification Xie et al.:

https://arxiv.org/abs/1911.04252

#ArtificialIntelligence #DeepLearning #MachineLearning

❇️ @AI_PythonEN
Productionizing #NLP Models

https://bit.ly/2OkdRAD

❇️ @AI_Python_EN
Correlation Coefficients in One Picture

❇️ @AI_PYTHON_EN
"SEMINAL DEBATE : YOSHUA BENGIO | GARY MARCUS" This Is The Debate The AI World Has Been Waiting For LIVE STREAMING :

https://www.eventbrite.ca/e/seminal-debate-yoshua-bengio-gary-marcus-live-streaming-tickets-81620778947

Date and Time : December 23, 2019 | 7:00 PM – 8:30 PM EST

#ArtificialIntelligence

❇️ @AI_Python_EN
A free linear algebra #textbook with solutions by Jim Hefferon. This knowledge will be very useful for understanding #machinelearning and beyond.

http://joshua.smcvt.edu/linearalgebra/#current_version

#book

❇️ @AI_Python_EN
Part of the communication challenges between data scientists and the business result from thinking one methodology is going to solve two problems. Illustrative example: The biz asks for a highly predictive churn model (this could be extended to many different use cases, but we're keeping it simple here). In reality, the biz wants to be able to:
1. Accurately identify customers with a high risk of churn so that they can implement some type of corrective measures.
2. They also want recommendations (based on data) that will inform what corrective measures could potentially have the biggest impact on reducing churn. To give the biz what they're expecting, it's possible that you'll need to build two separate models. (one that is highly predictive, the other that is easily interpretable). Bonus, once you've already collected the data, it's not that much incremental effort to build multiple models.
Agree or Disagree? And if you agree, are you already approaching things this way?

❇️ @AI_Python_EN
Machine ignoring = underfitting
Machine learning = optimal fitting
Machine memorization = overfitting

#datascience #machinelearning

❇️ @AI_Python_EN
How to Read Articles That Use Machine Learning Users’ Guides to the Medical Literature

https://jamanetwork.com/journals/jama/article-abstract/2754798

#machinelearning #paper #ArtificialIntelligence

❇️ @AI_Python_EN
A must read document for deep learning & machine learning practitioners

https://www.deeplearningbook.org/contents/guidelines.html

#deeplearning #machinelearning

❇️ @AI_Python_EN
Looking for Masters and PhD level students for Paylocity's data science internship program! Students must be in their penultimate year of school, with strong knowledge of machine learning and software engineering. You'll work with Paylocity's incredible talented Product Owners to translate our customers' business needs into data science needs and deliver features that enable next generation HR analytics.

https://2000recruiting.paylocity.com/recruiting/jobs/Details/2767/Paylocity/Data-Scientist-Intern---Summer-2020

❇️ @AI_Python_EN
Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity
Mandlekar et al.:
https://lnkd.in/fG9PGJK
Blog:
https://lnkd.in/fUjqAgH
Webpage:
https://lnkd.in/f5Vx6um
#Robotics #HumanComputerInteraction #MachineLearning

❇️ @AI_Python_EN
Decoding the Black Box: An Important Introduction to Interpretable Machine Learning Models in…

#machinelearning

https://bit.ly/2N5QFb3

❇️ @AI_PYTHON_EN
Mish is now even supported on YOLO v3 backend. Couldn't have been more elated with how rewarding this project has been. Link to repository -

https://github.com/digantamisra98/Mish

#neuralnetworks #mathematics #algorithms #deeplearning #machinelearning

❇️ @AI_Python_EN