Forwarded from Machinelearning
Building a Real Time Emotion Detection with Python
https://morioh.com/p/801c509dda99
Code: https://github.com/Dhanush45/Realtime-emotion-detectionusing-python
https://morioh.com/p/801c509dda99
Code: https://github.com/Dhanush45/Realtime-emotion-detectionusing-python
Forwarded from Machinelearning
Jukebox: a new generative model for audio from OpenAI.
Jukebox, a model that generates music with singing in the raw audio domain.
openai.com/blog/jukebox
Article: cdn.openai.com/papers/jukebox.pdf
Examples: https://jukebox.openai.com/
Code: https://github.com/openai/jukebox
Jukebox, a model that generates music with singing in the raw audio domain.
openai.com/blog/jukebox
Article: cdn.openai.com/papers/jukebox.pdf
Examples: https://jukebox.openai.com/
Code: https://github.com/openai/jukebox
OpenAI
Jukebox
Weβre introducing Jukebox, a neural net that generates music, including rudimentary singing, as raw audio in a variety of genres and artist styles. Weβre releasing the model weights and code, along with a tool to explore the generated samples.
Forwarded from Data Science Boom
Boom! Monthly selection from DSB. Issue #24
The TOP 10 most popular links of the month (April 2020)
1. 50 Must-Read Free Books For Every Data Scientist in 2020
https://bit.ly/2wTkLbl
2. $69 Trillion of World Debt in One Infographic
https://bit.ly/39JauM6
3. COVID-19 Dashboards
https://bit.ly/2xOf52p
4. 28 Jupyter Notebook Tips, Tricks, and Shortcuts
https://bit.ly/2Vi4ncs
5. The Seven Sins of Data Prep
https://bit.ly/2RvqgEd
6. Time Series Forecasting Best Practices & Examples
https://bit.ly/2K1g6GU
7. DataRobot (AutoML AI Platform) is opening the access to all COVID-19 researchers.
https://bit.ly/2w53Rpy
8. Beyond coronavirus: The path to the next normal
https://mck.co/2ymnsCn
9. My First Year as a Data Scientist
https://bit.ly/2UZwz3L
10. 10 Awesome Data Manipulation and Wrangling Hacks, Tips and Tricks
https://bit.ly/3497WFP
The TOP 10 most popular links of the month (April 2020)
1. 50 Must-Read Free Books For Every Data Scientist in 2020
https://bit.ly/2wTkLbl
2. $69 Trillion of World Debt in One Infographic
https://bit.ly/39JauM6
3. COVID-19 Dashboards
https://bit.ly/2xOf52p
4. 28 Jupyter Notebook Tips, Tricks, and Shortcuts
https://bit.ly/2Vi4ncs
5. The Seven Sins of Data Prep
https://bit.ly/2RvqgEd
6. Time Series Forecasting Best Practices & Examples
https://bit.ly/2K1g6GU
7. DataRobot (AutoML AI Platform) is opening the access to all COVID-19 researchers.
https://bit.ly/2w53Rpy
8. Beyond coronavirus: The path to the next normal
https://mck.co/2ymnsCn
9. My First Year as a Data Scientist
https://bit.ly/2UZwz3L
10. 10 Awesome Data Manipulation and Wrangling Hacks, Tips and Tricks
https://bit.ly/3497WFP
Forwarded from Data Science by ODS.ai π¦
Video lecture on geodesics
Geodesics generalize the idea of "straight lines" to curved spacesβlike the circular arc an airplane takes across the globe. This video gives a crash course on geodesics, using geometric algorithms to help tell the story.
Video: https://youtu.be/uojNGbVtlsQ
#closeenough #othermath
Geodesics generalize the idea of "straight lines" to curved spacesβlike the circular arc an airplane takes across the globe. This video gives a crash course on geodesics, using geometric algorithms to help tell the story.
Video: https://youtu.be/uojNGbVtlsQ
#closeenough #othermath
Forwarded from Data Science Boom
Online Seminar on Mathematical Foundations of Data Science
https://bit.ly/3bikw7x
7 Reasons To Not Hire a Data Scientist
https://bit.ly/2YBa48y
Donβt Fear the Robot
https://bit.ly/2WIGhrV
CNN Explainer. Learn Convolutional Neural Network (CNN) in your browser!
https://bit.ly/35LUqZu
My First Year as a Freelance AI Engineer
https://bit.ly/3clyNBV
https://bit.ly/3bikw7x
7 Reasons To Not Hire a Data Scientist
https://bit.ly/2YBa48y
Donβt Fear the Robot
https://bit.ly/2WIGhrV
CNN Explainer. Learn Convolutional Neural Network (CNN) in your browser!
https://bit.ly/35LUqZu
My First Year as a Freelance AI Engineer
https://bit.ly/3clyNBV
Forwarded from Data Science Boom
Using Neural Networks to Find Answers in Tables
https://bit.ly/2WLpHHQ
The Art of Storytelling in Analytics and Data Science | How to Create Data Stories?
https://bit.ly/3dHfBPs
AI and Efficiency
https://bit.ly/2Lq2wO0
The Nooscope Manifested. AI as Instrument of Knowledge Extractivism
https://bit.ly/2WNmcRw
Donβt Regulate Artificial Intelligence: Starve It
https://bit.ly/2WNNQ0G
https://bit.ly/2WLpHHQ
The Art of Storytelling in Analytics and Data Science | How to Create Data Stories?
https://bit.ly/3dHfBPs
AI and Efficiency
https://bit.ly/2Lq2wO0
The Nooscope Manifested. AI as Instrument of Knowledge Extractivism
https://bit.ly/2WNmcRw
Donβt Regulate Artificial Intelligence: Starve It
https://bit.ly/2WNNQ0G
Forwarded from Data Science by ODS.ai π¦
Abstraction and Reasoning Challenge winners
There is a very interesting challenge by #Francois Chollet about can a computer learn complex abstract tasks through maybe reasoning from a few examples?
And here is the first place with descriptions!
https://www.kaggle.com/c/abstraction-and-reasoning-challenge/discussion/154597
But author doubts about his solution brings us to AGI, but it's interesting to look through :)
"This DSL is solved by enumeration (exploiting duplicates) + a greedy stacking combiner. Everything is implemented efficiently in C++ (with no dependencies) and running in parallel."
There are 10k lines of code and a bunch of tricks that you can read about on the link.
Though second and third place also interesting β you can find it in discussion section here https://www.kaggle.com/c/abstraction-and-reasoning-challenge/discussion
The 3d place even almost don't use ML :)
So, nothing close to general reasoning here : )
#kaggle #chollet #AGI #stacking
There is a very interesting challenge by #Francois Chollet about can a computer learn complex abstract tasks through maybe reasoning from a few examples?
And here is the first place with descriptions!
https://www.kaggle.com/c/abstraction-and-reasoning-challenge/discussion/154597
But author doubts about his solution brings us to AGI, but it's interesting to look through :)
"This DSL is solved by enumeration (exploiting duplicates) + a greedy stacking combiner. Everything is implemented efficiently in C++ (with no dependencies) and running in parallel."
There are 10k lines of code and a bunch of tricks that you can read about on the link.
Though second and third place also interesting β you can find it in discussion section here https://www.kaggle.com/c/abstraction-and-reasoning-challenge/discussion
The 3d place even almost don't use ML :)
So, nothing close to general reasoning here : )
#kaggle #chollet #AGI #stacking
Forwarded from DataFlair
DEEP LEARNING PROJECT with PYTHON
An Extra Ordinary Project that everyone must try at least once π₯ππ―ππ»
https://data-flair.training/blogs/deep-surveillance-with-deep-learning-intelligent-video-surveillance-project/
An Extra Ordinary Project that everyone must try at least once π₯ππ―ππ»
https://data-flair.training/blogs/deep-surveillance-with-deep-learning-intelligent-video-surveillance-project/
DataFlair
Deep Surveillance with Deep Learning - Intelligent Video Surveillance Project - DataFlair
In this deep learning project, we will build a system to automate the task of analyzing video surveillance. We will analyze the video feed in real-time & identify any abnormal activities like violence or theft.
Forwarded from Daily Science to all
ScienceAlert - Latest
Vast Roman Town Abandoned Centuries Ago Revealed by Ground-Penetrating Radar
β @sciencetoall β
Vast Roman Town Abandoned Centuries Ago Revealed by Ground-Penetrating Radar
β @sciencetoall β
ScienceAlert
Vast Roman Town Abandoned Centuries Ago Revealed by Ground-Penetrating Radar
Once upon a time, Falerii Novi was a thriving community. For hundreds of years, generations of people strode its streets, lived out their lives under its roofs, shopped in its markets, and worshipped in its temples β from its founding in 241 BCE
Forwarded from DataFlair
AN INTERESTING PYTHON PROJECT
The easiest way to sharpen your Python skills π―ππ₯π
https://data-flair.training/blogs/project-in-python-colour-detection
The easiest way to sharpen your Python skills π―ππ₯π
https://data-flair.training/blogs/project-in-python-colour-detection
DataFlair
Project in Python - Colour Detection using Pandas & OpenCV - DataFlair
Python project on color detection - Learn to build an application that can detect the type of color by clicking on it with this interesting project in python using opencv & pandas.
Forwarded from Machinelearning
The Most Important Fundamentals of PyTorch you Should Know
https://blog.exxactcorp.com/the-most-important-fundamentals-of-pytorch-you-should-know/
Code: https://github.com/tirthajyoti/PyTorch_Machine_Learning
https://blog.exxactcorp.com/the-most-important-fundamentals-of-pytorch-you-should-know/
Code: https://github.com/tirthajyoti/PyTorch_Machine_Learning
Exxactcorp
Blog - the most important fundamentals of pytorch you should know | Exxact
Forwarded from Machinelearning
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Machine Learning in Dask
In this article you can learn how Dask works with a huge dataset on local machine or in a distributed manner.
https://www.kdnuggets.com/2020/06/machine-learning-dask.html
In this article you can learn how Dask works with a huge dataset on local machine or in a distributed manner.
https://www.kdnuggets.com/2020/06/machine-learning-dask.html
Forwarded from Machinelearning
Enhance your TensorFlow Lite deployment with Firebase
https://blog.tensorflow.org/2020/06/enhance-your-tensorflow-lite-deployment-with-firebase.html
https://blog.tensorflow.org/2020/06/enhance-your-tensorflow-lite-deployment-with-firebase.html
blog.tensorflow.org
Enhance your TensorFlow Lite deployment with Firebase
Learn how to use Firebase to deploy your TensorFlow Lite models over-the-air, monitor performance in production, and A/B test multiple model versions.
Forwarded from DataFlair
PYTHON for DATA SCIENCE
A Match made in Heaven π₯π―ππ€©ππ»
https://data-flair.training/blogs/learn-python-for-data-science/
A Match made in Heaven π₯π―ππ€©ππ»
https://data-flair.training/blogs/learn-python-for-data-science/
DataFlair
Learn Python for Data Science - 9 Essential Steps to become a Python developer - DataFlair
Learn Python for Data Science - Get ready to plan your journey of becoming a Python expert with DataFlair.
Forwarded from Machinelearning
Computer Vision using Tensorflow
https://levelup.gitconnected.com/computer-vision-using-tensorflow-946718d3c123
Full Code can be found on my Github
https://levelup.gitconnected.com/computer-vision-using-tensorflow-946718d3c123
Full Code can be found on my Github
Medium
Computer Vision using Tensorflow
Giving computers the ability to see through Machine Learning
Forwarded from Machinelearning
Extracting the main trend in a dataset: the Sequencer algorithm
The Sequencer is an algorithm that attempts to reveal the main sequence in a dataset, if it exists.
http://sequencer.org/
Github: https://github.com/dalya/Sequencer
Paper: https://arxiv.org/abs/2006.13948v1
The Sequencer is an algorithm that attempts to reveal the main sequence in a dataset, if it exists.
http://sequencer.org/
Github: https://github.com/dalya/Sequencer
Paper: https://arxiv.org/abs/2006.13948v1
Forwarded from DataFlair
Is Artificial Intelligence really gonna overpower Human Intelligence? π€βπ€·π»ββοΈπ―
https://data-flair.training/blogs/will-ai-replace-humans/
https://data-flair.training/blogs/will-ai-replace-humans/
DataFlair
Will AI replace Humans - Artificial Intelligence vs Human Intelligence - DataFlair
Will AI replace humans - Will human intelligence win the battle against Artificial intelligence or will AI lead the man power. Impact of AI on human.
Forwarded from Data Science by ODS.ai π¦
ββ(Re)Discovering Protein Structure and Function Through Language Modeling
Trained solely on unsupervised language modeling, the Transformer's attention mechanism recovers high-level structural (folding) and functional properties of proteins!
Why this is important: traditional protein modelling requires lots of computational power. This might be a key to more efficient structure modelling. Protein structure => function. Function => faster drug research and understanding of diseases mechanisms.
Blog: https://blog.einstein.ai/provis/
Paper: https://arxiv.org/abs/2006.15222
Code: https://github.com/salesforce/provis
#DL #NLU #proteinmodelling #bio #biolearning #insilico
Trained solely on unsupervised language modeling, the Transformer's attention mechanism recovers high-level structural (folding) and functional properties of proteins!
Why this is important: traditional protein modelling requires lots of computational power. This might be a key to more efficient structure modelling. Protein structure => function. Function => faster drug research and understanding of diseases mechanisms.
Blog: https://blog.einstein.ai/provis/
Paper: https://arxiv.org/abs/2006.15222
Code: https://github.com/salesforce/provis
#DL #NLU #proteinmodelling #bio #biolearning #insilico
Forwarded from Machinelearning
9 Key Machine Learning Algorithms Explained in Plain English
https://www.freecodecamp.org/news/a-no-code-intro-to-the-9-most-important-machine-learning-algorithms-today/
https://www.freecodecamp.org/news/a-no-code-intro-to-the-9-most-important-machine-learning-algorithms-today/
freeCodeCamp.org
9 Key Machine Learning Algorithms Explained in Plain English
By Nick McCullum Machine learning is changing the world. Google uses machine learning to suggest search results to users. Netflix uses it to recommend movies for you to watch. Facebook uses machine learning to suggest people you may know. Machine lea...