What’s New In Python 3.11
Next year Python’s version 2022
1. Enhanced error locations in tracebacks
2. Add math.cbrt(): return the cube root of x. (Contributed by Ajith Ramachandran in bpo-44357.)
3. On Windows, os.urandom() uses BCryptGenRandom() instead of CryptGenRandom() which is deprecated.
4.
Next year Python’s version 2022
1. Enhanced error locations in tracebacks
2. Add math.cbrt(): return the cube root of x. (Contributed by Ajith Ramachandran in bpo-44357.)
3. On Windows, os.urandom() uses BCryptGenRandom() instead of CryptGenRandom() which is deprecated.
4.
smtpd.MailmanProxy is now removed as it is unusable without an external module, mailmanKey Concepts in Deep Learning : Epoch In the context of training a model, epoch is a term used to refer to one iteration where the model sees the whole training set to update its weights.
Mini-batch gradient descent During the training phase, updating weights is usually not based on the whole training set at once due to computation complexities or one data point due to noise issues. Instead, the update step is done on mini-batches, where the number of data points in a batch is a hyperparameter that we can tune.
Loss function In order to quantify how a given model performs, the loss function L is usually used to evaluate to what extent the actual outputs y are correctly predicted by the model outputs Z
Cross-entropy loss In the context of binary classification in neural networks, the cross-entropy loss
Mini-batch gradient descent During the training phase, updating weights is usually not based on the whole training set at once due to computation complexities or one data point due to noise issues. Instead, the update step is done on mini-batches, where the number of data points in a batch is a hyperparameter that we can tune.
Loss function In order to quantify how a given model performs, the loss function L is usually used to evaluate to what extent the actual outputs y are correctly predicted by the model outputs Z
Cross-entropy loss In the context of binary classification in neural networks, the cross-entropy loss
pdfme
This is a powerful library to create PDF documents easily.
The way you create a PDF document with pdfme is very similar to how you create documents with LaTex
pip install pdfme
Docs and examples: https://pdfme.readthedocs.io
This is a powerful library to create PDF documents easily.
The way you create a PDF document with pdfme is very similar to how you create documents with LaTex
pip install pdfme
Docs and examples: https://pdfme.readthedocs.io
An AI device implanted at the brain’s surface has allowed a person with paralysis to communicate by converting his mental handwriting into text.
In that study, T5 set what was until now the all-time record: copying displayed sentences at about 40 characters per minute. Another study participant was able to write extemporaneously, selecting whatever words she wanted, at 24.4 characters per minute.
In that study, T5 set what was until now the all-time record: copying displayed sentences at about 40 characters per minute. Another study participant was able to write extemporaneously, selecting whatever words she wanted, at 24.4 characters per minute.
Manim is an animation engine for explanatory math videos.It's used to create precise animations programmatically, as demonstrated in the videos of 3Blue1Brown.
Aims to make all of PostgreSQL's awesome features available through the Django ORM. https://github.com/SectorLabs/django-postgres-extra
LaMDA is Google 's latest breakthrough in Natural Language Understanding.
LaMDA stands for "Language Model for Dialogue Applications".
It has been designed to converse on any topic from Pluto to Paper Plane.
The below video shows a demo of the conversation, its really exciting.
Following from previous models such as BERT and GPT-3, LaMDA is also based on the Transformer Architecture.
What makes LaMDA different is its "open ended nature".
What does that mean?
Human conversations have chaotic features.
It implies that we can start a conversation with one topic and end up in a very different one a few minutes later.
LaMDA can actually tackle such situations and perfectly engage in natural conversations with people.
LaMDA stands for "Language Model for Dialogue Applications".
It has been designed to converse on any topic from Pluto to Paper Plane.
The below video shows a demo of the conversation, its really exciting.
Following from previous models such as BERT and GPT-3, LaMDA is also based on the Transformer Architecture.
What makes LaMDA different is its "open ended nature".
What does that mean?
Human conversations have chaotic features.
It implies that we can start a conversation with one topic and end up in a very different one a few minutes later.
LaMDA can actually tackle such situations and perfectly engage in natural conversations with people.
AMAZING website - "Deep Learning Drizzle"
It is a constantly-updated list of machine learning/deep learning course materials that are taught by domain experts and are available for FREE!
Check it out here →
https://deep-learning-drizzle.github.io/
It is a constantly-updated list of machine learning/deep learning course materials that are taught by domain experts and are available for FREE!
Check it out here →
https://deep-learning-drizzle.github.io/
Announcement — PyTorch Developer Day 2021! Application and Call for Content are now open
Technical Talks Live Stream - December 1, 2021
Poster Exhibition & Networking - December 2, 2021
Technical Talks Live Stream - December 1, 2021
Poster Exhibition & Networking - December 2, 2021
On device machine learning is going to be the way forward 🤖
🍎Apple devices have their own neural engine.
🔢 Google is making the tensor processor.
📱Samsung is working with AMD to bring rDNA GPUs to the Exynos processors.
The future is bright!
🍎Apple devices have their own neural engine.
🔢 Google is making the tensor processor.
📱Samsung is working with AMD to bring rDNA GPUs to the Exynos processors.
The future is bright!
Did you know that the #
Python style guide (PEP8) offers guidance on how you ought to import multiple modules?
Python style guide (PEP8) offers guidance on how you ought to import multiple modules?
Every week, the top AI labs globally — Google, Facebook, Microsoft, Apple, etc. — release tons of new ML research work, tools, datasets, models, libraries and frameworks.
Interestingly, they all seem to have picked a particular school of thought in deep learning. With time, this pattern is becoming more and more clear.
DeepMind remains synonymous with reinforcement learning. From AlphaGo to MuZero and the recent AlphaFold, the company has been championing breakthroughs in reinforcement learning.
Google is advancing AutoML in highly diverse areas like time-series analysis and computer vision.
Apple, in the last few years, has ventured into federated learning.
Microsoft Research is pioneering machine teaching research and technology in computer vision and speech analysis.
Amazon has become one of the leading research hubs for transfer learning methods due to its exceptional work in the Alexa digital assistant.
IBM is pushing its research boundaries in quantum machine learning.
Interestingly, they all seem to have picked a particular school of thought in deep learning. With time, this pattern is becoming more and more clear.
DeepMind remains synonymous with reinforcement learning. From AlphaGo to MuZero and the recent AlphaFold, the company has been championing breakthroughs in reinforcement learning.
Google is advancing AutoML in highly diverse areas like time-series analysis and computer vision.
Apple, in the last few years, has ventured into federated learning.
Microsoft Research is pioneering machine teaching research and technology in computer vision and speech analysis.
Amazon has become one of the leading research hubs for transfer learning methods due to its exceptional work in the Alexa digital assistant.
IBM is pushing its research boundaries in quantum machine learning.
*** Big Breaking ***
Python 3.10 is released today! pythonistas. 🐍 🎊
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Python 3.10 is released today! pythonistas. 🐍 🎊
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