Machine Learning @machine_ml
We retweet everything related to #MachineLearning Coursera Courses: ML: https://t.co/O5zMn4gyVO DL: https://t.co/vEmZPkbRzB NLP: https://t.co/nkyrR13HJu More : https://t.co/TogJrn0KDI Joined June 2018-
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What are some great bots you have interacted on any website or portal? Would love to explore them, I haven't seen any fully functional and intelligent bot till now even on big websites.
Here is the list of the great NLP courses.
Here is the list of the great NLP courses.
With just one month to go until the next iteration of the FSDL course, we think it's high time to bring back 🛠️ Tooling Tuesday 🛠️ and focus on some of the new tools we're bringing in for the 2022 version of the course. This will serve as a Thread of Threads.
Folks, this is an opportunity to learn from one the best Deep Learning course.
Folks, this is an opportunity to learn from one the best Deep Learning course.
Free alternative for Colab similar to AWS Studio, you can apply for wait list. Here are FAQs: studiolab.sagemaker.aws/faq
Free alternative for Colab similar to AWS Studio, you can apply for wait list. Here are FAQs: studiolab.sagemaker.aws/faq
Read thoughts from Sayak about learning ML.
Folks, utilize it to the best.
A free Deep Learning course using Pytorch and starting at the very beginning. Includes some cool stuff: • Transformers • Generative models • Self-supervised learning Check the attached overview. deeplearning.neuromatch.io/tutorials/intr…
Having a baseline model gives a better picture for futher steps. AutoML(much powerful than just for baseline) such as PyCaret and @h2oai can be one way to build your first simple baseline with minimum code.
Having a baseline model gives a better picture for futher steps. AutoML(much powerful than just for baseline) such as PyCaret and @h2oai can be one way to build your first simple baseline with minimum code.
Great resources to help you with Data Science stuff at one place, do checkout.
Hey folks, please let us know what kind of content you all want from this account going forward?
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RT @hubofml: RT @awscloud: The machines are taking over. 🙃 Join us as we showcase the many ways #AWS AI & #MachineLearning are helping our customers innovate, accommodate, calculate, & motivate to drive their businesses forward. 🔗 …
RT @xaelbot: RT @avikumart_: Day 14 of #100DaysOfCode ML series: >> Support vector machine is one of the most important classification algorithms🐍🤖👍 >> SVM's implementation in python is very much easier to grasp (SEE BELOW👇) #Python #MachineLearn…
RT @hubofml: RT @avikumart_: Day 14 of #100DaysOfCode ML series: >> Support vector machine is one of the most important classification algorithms🐍🤖👍 >> SVM's implementation in python is very much easier to grasp (SEE BELOW👇) #Python #MachineLearn…
RT @bot_tensorflow: RT @cousesites1: DP-100: A-Z Machine Learning using Azure Machine Learning #udemycoupon => onlinecoursesnet.blogspot.com/2021/08/dp-100… #MachineLearning #DeepLearning #python #datascience #TensorFlow #FinancialAnalysis #rstats #iiot #iot #javascript #ai #womenintech #100DaysO…
RT @alljstweet: RT @abirnaym: Open source is a revolution. It shaped the tech ecosystem you live in. Here are 5 Open Source technology that changed the world: 👇 1. Linux 2. Android 3. Databases 4. Machine Learning Libraries 5. Web frameworks #100DaysOfCode #100Devs #Pyth…
RT @Jigneshkevat: RT @awscloud: The machines are taking over. 🙃 Join us as we showcase the many ways #AWS AI & #MachineLearning are helping our customers innovate, accommodate, calculate, & motivate to drive their businesses forward. 🔗 …
RT @LebotPython: RT @avikumart_: Day 14 of #100DaysOfCode ML series: >> Support vector machine is one of the most important classification algorithms🐍🤖👍 >> SVM's implementation in python is very much easier to grasp (SEE BELOW👇) #Python #MachineL…
Machine Learning FLX @machinelearnflx
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298K Followers 1K Following Research Scientist at DeepMind. Opinions my own. Inventor of GANs. Lead author of https://t.co/M6vl8pEifa🎓 Getting Started with Transformers Transformer is one of the most important concepts in ML and NLP today. I created this guide for students that want to get started with transformers. github.com/dair-ai/Transf…
A free Deep Learning course using Pytorch and starting at the very beginning. Includes some cool stuff: • Transformers • Generative models • Self-supervised learning Check the attached overview. deeplearning.neuromatch.io/tutorials/intr…
A common mistake that people starting with machine learning make: They start building a model without defining a baseline first. You need something simpler first. Even if manual or random. Only then you should start building a model.
Just found this amazing Data Set on Kaggle. It has almost all the things you will ever need for data science starting from maths and stats to ml, dl, docker, git, etc. Total 251 files: 194 pdfs 23 images 34 in another format kaggle.com/datasets/timob…
@machine_ml teaching python ,step by step with infographic. 🙏 in advance
@machine_ml @cybersec_feeds @elizabot9 @Grepnetics Keep up the good work👍👍👍
Got my first COVID-19 shot! Still need to wear mask and social distance of course. Be safe everyone!
🚨Transformers is expanding to Speech!🚨 🤗Transformers v4.3.0 is out and we are excited to welcome @FacebookAI's Wav2Vec2 as the first Automatic Speech Recognition model to our library! 👉Now, you can transcribe your audio files directly on the hub: huggingface.co/facebook/wav2v…
For folks trying to get their head around PEP 634 (pattern matching), which will land in the next alpha release of 3.10, here's a brief tutorial I wrote: (more concise than the introduction in PEP 636): github.com/gvanrossum/pat…
Some interesting Text Classification Datasets Easily Available from @huggingface's datasets python package pulled out in the thread below, ordered by size. (Thread)
🎉 Introducing... Datasets! We are now indexing 3000+ research datasets from machine learning. Find datasets by task and modality, compare usage over time, browse benchmarks, and much more! Explore the catalogue here: paperswithcode.com/datasets
Wonder why AI models powered by neural nets are so magical? The laws of physics dictate that the universe is governed by a tiny subset of all possible functions i.e. Patterns repeat themselves everywhere NNs learn to approximate the functions that represent these patterns
Statistician: Do you ever use statistics? ML researcher: Nope. Never. Statistician: What about when reading a paper? ML: Nope. Never. Statistician: Ok. So if you’re reading an ML paper comparing lots of models, how do you know which one is the best? ML: Bold font.
Top Data Science, ML, AI and DL courses from Coursera, DataCamp and top universities. 1. Data Science Professional Certificate: bit.ly/2FpsX48 2. Machine Learning: bit.ly/2ZKwQIG 3. Deep Learning: bit.ly/360eDKx 4. Data Science: bit.ly/2XTzBId
Bottleneck Transformers for Visual Recognition SotA visual recognition model with convolution+attention that outperforms EfficientNet and DeiT in terms of performance-computes trade-off. arxiv.org/abs/2101.11605
Question Answer Bot using BERT & sQuAD: cdQA w/ India Tourist Guides It uses BERT pre-trained model for the QA purpose, in this notebook question answering has been achieved using cdQA library. Link: kaggle.com/satyampd/quest… #machinelearning #100DaysOfCode #kaggle #DataScience
The latest #ethicalbrand Daily! daily.ethicalbrand.com/?edition_id=35… Thanks to @BillionaireBBD @FocusBand @machine_ml
Using physics-informed machine learning techniques to (better) make/simulate wildfire spread predictions show promising results READ arxiv.org/pdf/2012.06825… @unito @machine_ml @DOIWildlandFire @NCAR_Science #LANDFIRE data used landfire.gov/fbfm13.php @NatureClimate @USFireCentral
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