UnhypedAI @UnhypedAI

We are here to unhype Mathematics, Data science and Machine learning concepts and make you fall in love with them just like we did. Joined September 2021

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DAIR.AI @dair_ai

2 years ago

Top ML Papers of the Week (July 10 - July 16): - CM3Leon - LongLLaMA - AnimateDiff - Patch n’ Pack: NaViT - Secrets of RLHF in LLMs - LLMs as General Pattern Machines ...

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Thomas Wolf @Thom_Wolf

3 years ago

ChatGPT makes me both very excited and worried about the future of AI

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UnhypedAI @UnhypedAI

3 years ago

This is gonna be huge! #PyTorch

PyTorch @PyTorch

3 years ago

This is gonna be huge! #PyTorch

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Stanford AI Lab @StanfordAILab

3 years ago

At least we’re only beaten by a non-American university 🤣

Science Is Strategic @scienceisstrat1

3 years ago

At least we’re only beaten by a non-American university 🤣

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UnhypedAI @UnhypedAI

3 years ago

"Practical Deep Learning for Coders" - latest version of this free course is released by @fastdotai This clearly is treasure chest for new learners. Course link: course.fast.ai Thanks @jeremyphoward

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UnhypedAI @UnhypedAI

4 years ago

Check out the 5 alternatives of Pandas Dataframe apply() #Python #Pythonprogramming #WomenWhoCode #DataScience

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Let's kick off 2⃣0⃣2⃣2⃣ with some awesome, free resources to accelerate your cloud & DevOps careers 🚀 Here are 2⃣3⃣ free tutorials, courses, videos, repositories, channels, etc. that cover AWS, Azure, GCP, DevOps, Cloud essentials, Linux & much more! 🔥🔥🔥 🧵👇

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UnhypedAI @UnhypedAI

4 years ago

Python dunder methods are methods that have a name starting and ending with Double UNDERscore. These methods are what hook syntax(e.g.,using +)with your own code. Some common egs are __init__, __add__, __str__, etc. What's the last dunder you learned about ? #Python #WomenWhoCode

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UnhypedAI @UnhypedAI

4 years ago

The Seam Carving algorithm for content-aware image resizing. The algorithm finds the seam (continuous sequence of pixels) with the smallest contribution to the image content and then removes it (carves it out). #AI #Image #Python #ComputerVision #Algorithms

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UnhypedAI @UnhypedAI

4 years ago

Important skill for a data science enthusiast! How to read a published paper kdnuggets.com/2021/10/learn-… #DataScientist #AI #DataScience #learning #WomenWhoCode

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François Chollet @fchollet

4 years ago

Announcement: my book Deep Learning with Python (2nd edition) has been released. 500 pages of code examples, theory, context, practical tips... If you want to really understand how deep learning works, why it matters, and how to use it, this is your book! manning.com/books/deep-lea…

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UnhypedAI @UnhypedAI

4 years ago

Dynamic Programming - break down the problem into subproblems and reuse the results of subproblems. Climbing Stairs Problem leetcode.com/problems/climb… #leetcode #100DaysOfCode #Interviews

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UnhypedAI @UnhypedAI

4 years ago

Look Stupid danluu.com/look-stupid/

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Santiago @svpino

4 years ago

Practical machine learning recipe: 1. Understand the problem 2. Determine performance goal 3. Collect and prepare data 4. Compute a baseline 5. Build a model that beats it From this point, iterate until "good enough": 6. Tune your data and model 7. Measure, update baseline

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UnhypedAI @UnhypedAI

4 years ago

We all get stuck sometimes. Whether it’s an academic rut, or personal tribulations. Thanks to such amazing quality content for anybody to pickup skills. #LearnProgramming

freeCodeCamp.org @freeCodeCamp

4 years ago

We all get stuck sometimes. Whether it’s an academic rut, or personal tribulations. Thanks to such amazing quality content for anybody to pickup skills. #LearnProgramming

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UnhypedAI @UnhypedAI

4 years ago

The 3M's in #statistics The Mean is the average of a data set. The Mode is the most common number in a data set. The Median is the middle of the set of numbers. #Python #interview

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Tom Goldstein @tomgoldsteincs

4 years ago

This awesome @distillpub article will make you feel like you understand Gaussian Processes 🧐 distill.pub/2019/visual-ex… Then, this awesome book will make you realize that you just don’t 😵‍💫 math.uci.edu/~rvershyn/pape…