Most common pitfalls, you can encounter when training neural network.
http://telegra.ph/Most-common-neural-network-mistakes-07-01
#beginner #novice #dl #tutorial
http://telegra.ph/Most-common-neural-network-mistakes-07-01
#beginner #novice #dl #tutorial
Telegraph
Most common neural network mistakes
You didn't try to overfit a single batch first You forgot to toggle train/eval mode for the net You forgot to .zero_grad() (in pytorch) before .backward() You passed softmaxed outputs to a loss that expects raw logits You didn't use `bias=False` for yourβ¦
Deep Learning for Matching in Search and Recommendation
PDF: http://www.comp.nus.edu.sg/~xiangnan/sigir18-deep.pdf
#sigir2018 #Tutorial
PDF: http://www.comp.nus.edu.sg/~xiangnan/sigir18-deep.pdf
#sigir2018 #Tutorial
Complete code examples for Machine Translation with Attention, Image Captioning, Text Generation, and DCGAN implemented with tf.keras and eager execution
βComplete code examples for Machine Translation with Attention, Image Captioning, Text Generationβ¦β https://medium.com/tensorflow/complete-code-examples-for-machine-translation-with-attention-image-captioning-text-generation-51663d07a63d
#tensorflow #tutorial
βComplete code examples for Machine Translation with Attention, Image Captioning, Text Generationβ¦β https://medium.com/tensorflow/complete-code-examples-for-machine-translation-with-attention-image-captioning-text-generation-51663d07a63d
#tensorflow #tutorial
Medium
Complete code examples for Machine Translation with Attention, Image Captioning, Text Generation, and DCGAN implemented with tf.kerasβ¦
By Yash Katariya, Developer Programs Engineer Intern
Deploying a Machine Learning Model as a REST API
Yet another #tutorial on how to serve #production model with flask.
Link: https://towardsdatascience.com/deploying-a-machine-learning-model-as-a-rest-api-4a03b865c166
Github repo: https://github.com/mnguyenngo/flask-rest-setup/tree/master/sentiment-clf
Yet another #tutorial on how to serve #production model with flask.
Link: https://towardsdatascience.com/deploying-a-machine-learning-model-as-a-rest-api-4a03b865c166
Github repo: https://github.com/mnguyenngo/flask-rest-setup/tree/master/sentiment-clf
Medium
Deploying a Machine Learning Model as a REST API
As a Python developer and data scientist, I have a desire to build web apps to showcase my work. As much as I like to design the front-endβ¦
A set of best where-to-start-with-python resources.
This is the collection of beginners resources from a tweet by fast.ai cofounder, covering any resource which helped people to learn python from scratch.
https://telegra.ph/A-collection-of-where-to-start-python-resources-11-05
#beginner #novice #CS #python #tutorial
This is the collection of beginners resources from a tweet by fast.ai cofounder, covering any resource which helped people to learn python from scratch.
https://telegra.ph/A-collection-of-where-to-start-python-resources-11-05
#beginner #novice #CS #python #tutorial
Telegraph
A collection of where-to-start python resources
CodeAcademy (learn through practice) https://jeffknupp.com Python Numpy Tutorial as ipynb file Learn Python The Hard Way PyVideo Youtube playlist MIT open cource Rosalind (learn through practice platform) Coursera Python for everybody specialisation Pythonβ¦
Deep learning for NLP crash course at ABBYY.
Github repo with scheduled plan for learning #DL #NLP online.
Link: https://github.com/DanAnastasyev/DeepNLP-Course
#educational #tutorial #course #beginner #novice #entrylevel
Github repo with scheduled plan for learning #DL #NLP online.
Link: https://github.com/DanAnastasyev/DeepNLP-Course
#educational #tutorial #course #beginner #novice #entrylevel
GitHub
GitHub - DanAnastasyev/DeepNLP-Course: Deep NLP Course
Deep NLP Course. Contribute to DanAnastasyev/DeepNLP-Course development by creating an account on GitHub.
Using Nucleus and TensorFlow for DNA Sequencing Error Correction
This is a new #tutorial of the Genomics team in #GoogleBrain. Good place to start with #deeplearning for #genomics using Nucleus and #Tensorflow.
Link: https://medium.com/tensorflow/using-nucleus-and-tensorflow-for-dna-sequencing-error-correction-47f3f7fc1a50
Google colab: https://colab.research.google.com/github/google/nucleus/blob/master/nucleus/examples/dna_sequencing_error_correction.ipynb
#Google #healthcare
This is a new #tutorial of the Genomics team in #GoogleBrain. Good place to start with #deeplearning for #genomics using Nucleus and #Tensorflow.
Link: https://medium.com/tensorflow/using-nucleus-and-tensorflow-for-dna-sequencing-error-correction-47f3f7fc1a50
Google colab: https://colab.research.google.com/github/google/nucleus/blob/master/nucleus/examples/dna_sequencing_error_correction.ipynb
#Google #healthcare
Medium
Using Nucleus and TensorFlow for DNA Sequencing Error Correction
Posted by Gunjan Baid, Helen Li, and Pi-Chuan Chang
Really short and brief, yet useful #tutorial on #PyTorch #transferlearning
Transfer learning is a concept of using network trained for a certain task for another one.
Link: https://medium.com/@iamHarin17/transfer-learning-in-pytorch-f7736598b1ed
#DL #novice #entrylevel #beginner
Transfer learning is a concept of using network trained for a certain task for another one.
Link: https://medium.com/@iamHarin17/transfer-learning-in-pytorch-f7736598b1ed
#DL #novice #entrylevel #beginner
Medium
Implementing Transfer Learning in PyTorch
Transfer Learning is a technique where a model trained for a certain task is used for another similar task.
#Google has open-sourced #FederatedLearning code
Step-by-step #tutorial showing how to perform Federated Learning using the same infrastructure Google
uses on 10s of millions of smartphones.
Link: https://medium.com/tensorflow/introducing-tensorflow-federated-a4147aa20041
Step-by-step #tutorial showing how to perform Federated Learning using the same infrastructure Google
uses on 10s of millions of smartphones.
Link: https://medium.com/tensorflow/introducing-tensorflow-federated-a4147aa20041
Medium
Introducing TensorFlow Federated
Posted by Alex Ingerman (Product Manager) and Krzys Ostrowski (Research Scientist)
A Recipe for Training Neural Networks by Andrej Karpathy
New article written by Andrej Karpathy distilling a bunch of useful heuristics for training neural nets. The post is full of real-world knowledge and how-to details that are not taught in books and often take endless hours to learn the hard way.
Link: https://karpathy.github.io/2019/04/25/recipe/
#tipsandtricks #karpathy #tutorial #nn #ml #dl
New article written by Andrej Karpathy distilling a bunch of useful heuristics for training neural nets. The post is full of real-world knowledge and how-to details that are not taught in books and often take endless hours to learn the hard way.
Link: https://karpathy.github.io/2019/04/25/recipe/
#tipsandtricks #karpathy #tutorial #nn #ml #dl
karpathy.github.io
A Recipe for Training Neural Networks
Musings of a Computer Scientist.
ββπ£ Conversational AI building tutorial, open-source code & demo!
Building a SOTA Conversational AI with transfer learning & OpenAI GPT models
Code/pretrained model from NeurIPS 2018 ConvAI2 competition model, SOTA on automatic track
Detailed Tutorial w. code
Tutorial: https://medium.com/huggingface/how-to-build-a-state-of-the-art-conversational-ai-with-transfer-learning-2d818ac26313
Demo: http://convai.huggingface.co
Code: https://github.com/huggingface/transfer-learning-conv-ai
#tutorial #novice
Building a SOTA Conversational AI with transfer learning & OpenAI GPT models
Code/pretrained model from NeurIPS 2018 ConvAI2 competition model, SOTA on automatic track
Detailed Tutorial w. code
Tutorial: https://medium.com/huggingface/how-to-build-a-state-of-the-art-conversational-ai-with-transfer-learning-2d818ac26313
Demo: http://convai.huggingface.co
Code: https://github.com/huggingface/transfer-learning-conv-ai
#tutorial #novice
ββGANs from Scratch 1: A deep introduction.
Great introduction and tutorial. With code in PyTorch and TensorFlow
Link: https://medium.com/ai-society/gans-from-scratch-1-a-deep-introduction-with-code-in-pytorch-and-tensorflow-cb03cdcdba0f
#tensorflow #pytorch #GAN #tutorial #entrylevel #novice #wheretostart
Great introduction and tutorial. With code in PyTorch and TensorFlow
Link: https://medium.com/ai-society/gans-from-scratch-1-a-deep-introduction-with-code-in-pytorch-and-tensorflow-cb03cdcdba0f
#tensorflow #pytorch #GAN #tutorial #entrylevel #novice #wheretostart
Big scandal on popular YouTuber ML course
Siraj Raval, who raised his audience on devliering various YouTube videos, explaning #ML and #DL concepts as long with interviews with leading persons, launched his own course, but failed to provide much value.
His course was built on open and free tutorials, created by passionate enthusiasts, but he failed to attribute them properly and charged money for ununique content without any proper support for students.
He also oversold his course and tried to hide that from students, claiming to provide personal feedbacks, but failing to do so due to being too greedy.
Most of the best online courses and study programms are available online and for free, including those, we gathered here on our channel and attributed with hastags #wheretostart #entrylevel #MOOC #tutorial. Feel free to click these hashtags and browse for best available resources to start learning data science.
Link: https://www.theregister.co.uk/AMP/2019/09/27/youtube_ai_star
Siraj Raval, who raised his audience on devliering various YouTube videos, explaning #ML and #DL concepts as long with interviews with leading persons, launched his own course, but failed to provide much value.
His course was built on open and free tutorials, created by passionate enthusiasts, but he failed to attribute them properly and charged money for ununique content without any proper support for students.
He also oversold his course and tried to hide that from students, claiming to provide personal feedbacks, but failing to do so due to being too greedy.
Most of the best online courses and study programms are available online and for free, including those, we gathered here on our channel and attributed with hastags #wheretostart #entrylevel #MOOC #tutorial. Feel free to click these hashtags and browse for best available resources to start learning data science.
Link: https://www.theregister.co.uk/AMP/2019/09/27/youtube_ai_star
www.theregister.co.uk
YouTuber charged loads of fans $199 for shoddy machine-learning course that copy-pasted other people's GitHub code
Oh, and there wasn't a refund policy until folk complained
ββNew tutorial on QA task
The T5 team competed against T5 in a "pub quiz" on (context-free) questions from the TriviaQA/NQ validation sets.
Result: team got 20% right; T5 got 35%.
Colab link: https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/master/notebooks/t5-trivia.ipynb
Source: twitter
#NLU #NLP #Colab #Tutorial #QA
The T5 team competed against T5 in a "pub quiz" on (context-free) questions from the TriviaQA/NQ validation sets.
Result: team got 20% right; T5 got 35%.
Colab link: https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/master/notebooks/t5-trivia.ipynb
Source: twitter
#NLU #NLP #Colab #Tutorial #QA
P-value, explained, one more time with demos
Article includes not only great explanation of what is #pvalue, but how it works and how it can be used to make a correct conclusions.
Link:https://www.freecodecamp.org/news/what-is-statistical-significance-p-value-defined-and-how-to-calculate-it/
#entrylevel #dsformanagers #tutorial #explained #interactive #statistics
Article includes not only great explanation of what is #pvalue, but how it works and how it can be used to make a correct conclusions.
Link:https://www.freecodecamp.org/news/what-is-statistical-significance-p-value-defined-and-how-to-calculate-it/
#entrylevel #dsformanagers #tutorial #explained #interactive #statistics
freeCodeCamp.org
What is Statistical Significance? P Value Defined and How to Calculate It
By Peter Gleeson P values are one of the most widely used concepts in statistical analysis. They are used by researchers, analysts and statisticians to draw insights from data and make informed decisions. Along with statistical significance, they are...
ββTutorial on Generative Adversarial Networks (GANs) with Keras and TensorFlow
Nice tutorial with enough theory to understand what you are doing and code to get it done.
Link: https://www.pyimagesearch.com/2020/11/16/gans-with-keras-and-tensorflow/
#Keras #TensorFlow #tutorial #wheretostart #GAN
Nice tutorial with enough theory to understand what you are doing and code to get it done.
Link: https://www.pyimagesearch.com/2020/11/16/gans-with-keras-and-tensorflow/
#Keras #TensorFlow #tutorial #wheretostart #GAN
Forwarded from Machinelearning
Π Π΅ΠΏΠΎΠ·ΠΈΡΠΎΡΠΈΠΉ Π½Π° Github c Π½Π°Π±ΠΎΡΠΎΠΌ ipynb-ΡΡΡΠΎΡΠΈΠ°Π»ΠΎΠ² ΠΏΠΎ Prompt Engineering Π΄Π»Ρ ΠΎΡΠ²ΠΎΠ΅Π½ΠΈΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΡ ΠΏΡΠΎΠΌΠΏΡΠΎΠ² Π΄Π»Ρ ΠΌΠΎΠ΄Π΅Π»ΠΈ Qwen2.5-14B.
Π ΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²ΠΎ ΡΠ°Π·Π΄Π΅Π»Π΅Π½ΠΎ Π½Π° 9 Π³Π»Π°Π² Ρ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΡΠΏΡΠ°ΠΆΠ½Π΅Π½ΠΈΡΠΌΠΈ ΠΈ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅ΠΌ Ρ "ΠΏΡΠΎΠ΄Π²ΠΈΠ½ΡΡΡΠΌΠΈ" ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ. Π ΠΊΠ°ΠΆΠ΄ΠΎΠΉ Π³Π»Π°Π²Π΅ Π΅ΡΡΡ "Example Playground" Π΄Π»Ρ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠΎΠ² Ρ ΠΏΡΠΈΠΌΠ΅ΡΠ°ΠΌΠΈ ΠΈ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ Π·Π° ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡΠΌΠΈ Π² ΠΈΠ½ΡΠ΅ΡΠ΅Π½ΡΠ΅ Ollama.
Π ΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅Ρ ΠΌΠΎΠ΄Π΅Π»Ρ Qwen 2.5-14B, Π½ΠΎ Π²ΡΠ΅ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΏΠΎΠ΄Ρ ΠΎΠ΄ΡΡ ΠΈ Π΄Π»Ρ ΠΌΠΎΠ΄Π΅Π»ΠΈ Qwen 2.5-7B.
ΠΠ°ΡΠ°Π»ΡΠ½ΡΠΉ ΡΡΠΎΠ²Π΅Π½Ρ
Π‘ΡΠ΅Π΄Π½ΠΈΠΉ ΡΡΠΎΠ²Π΅Π½Ρ
ΠΡΠΎΠ΄Π²ΠΈΠ½ΡΡΡΠΉ ΡΡΠΎΠ²Π΅Π½Ρ
ΠΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅: ΠΠ° ΠΏΡΠ΅Π΄Π΅Π»Π°ΠΌΠΈ ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΡΡ ΠΏΠΎΠ΄ΡΠΊΠ°Π·ΠΎΠΊ
@ai_machinelearning_big_data
#AI #ML #LLM #Github #Tutorial #Ollama
Please open Telegram to view this post
VIEW IN TELEGRAM
Forwarded from Machinelearning
1. Π ΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²ΠΎ ΠΏΠΎ Π΄ΠΈΡΡΠΈΠ»Π»ΡΡΠΈΠΈ ΠΎΡ OpenAI
Π ΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΠΏΠΎΠ΄ΡΠΎΠ±Π½ΠΎΠ΅ ΠΎΠΏΠΈΡΠ°Π½ΠΈΠ΅ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π·Π½Π°Π½ΠΈΠΉ ΠΎΡ Π±ΠΎΠ»Π΅Π΅ ΠΊΡΡΠΏΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΊ ΠΊΠΎΠΌΠΏΠ°ΠΊΡΠ½ΠΎΠΉ, c ΡΠΎΡ ΡΠ°Π½Π΅Π½ΠΈΠ΅ΠΌ Π²ΡΡΠΎΠΊΠΎΠΉ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ.
ΠΡΠ½ΠΎΠ²Π½ΡΠ΅ Π°ΡΠΏΠ΅ΠΊΡΡ, ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Π½ΡΠ΅ Π² ΡΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²Π΅:
- Π‘ΠΎΡ ΡΠ°Π½Π΅Π½ΠΈΠ΅ Π²ΡΡ ΠΎΠ΄Π½ΡΡ Π΄Π°Π½Π½ΡΡ ΠΊΡΡΠΏΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ: Π‘ΠΎΠ·Π΄Π°Π½ΠΈΠ΅ Π½Π°Π±ΠΎΡΠ° Π΄Π°Π½Π½ΡΡ , ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π³ΠΎ ΠΏΡΠ΅Π΄ΡΠΊΠ°Π·Π°Π½ΠΈΡ Π±ΠΎΠ»ΡΡΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ Π±ΡΠ΄ΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡΡΡ Π΄Π»Ρ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ ΠΌΠ΅Π½ΡΡΠ΅ΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ.
- ΠΡΠ΅Π½ΠΊΠ° ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ: Π‘ΡΠ°Π²Π½ΠΈΡΠ΅Π»ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΠΎΡΠ½ΠΎΡΡΠΈ ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΊΠ°ΠΊ ΠΊΡΡΠΏΠ½ΠΎΠΉ, ΡΠ°ΠΊ ΠΈ ΠΊΠΎΠΌΠΏΠ°ΠΊΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ ΠΌΠ΅ΡΡΠΈΠΊ.
- Π‘ΠΎΠ·Π΄Π°Π½ΠΈΠ΅ ΠΎΠ±ΡΡΠ°ΡΡΠΈΡ Π΄Π°Π½Π½ΡΡ Π΄Π»Ρ ΠΊΠΎΠΌΠΏΠ°ΠΊΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ: ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠ΅Π΄ΡΠΊΠ°Π·Π°Π½ΠΈΠΉ ΠΊΡΡΠΏΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π΄Π»Ρ Π³Π΅Π½Π΅ΡΠ°ΡΠΈΠΈ ΠΎΠ±ΡΡΠ°ΡΡΠ΅Π³ΠΎ Π½Π°Π±ΠΎΡΠ° Π΄Π°Π½Π½ΡΡ , ΡΠΏΠΎΡΠΎΠ±ΡΡΠ²ΡΡΡΠ΅Π³ΠΎ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠΌΡ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ ΠΌΠ΅Π½ΡΡΠ΅ΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ.
- ΠΡΠ΅Π½ΠΊΠ° Π΄ΠΎΠΎΠ±ΡΡΠ΅Π½Π½ΠΎΠΉ ΠΊΠΎΠΌΠΏΠ°ΠΊΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ: ΠΡΠΎΠ²Π΅ΡΠΊΠ° ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΈ ΡΠΎΡΠ½ΠΎΡΡΠΈ ΠΊΠΎΠΌΠΏΠ°ΠΊΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΠΎΡΠ»Π΅ ΠΏΡΠΎΡΠ΅ΡΡΠ° Π΄ΠΈΡΡΠΈΠ»Π»ΡΡΠΈΠΈ Π΄Π»Ρ ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π΅Π½ΠΈΡ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΡ ΡΡΠ΅Π±ΠΎΠ²Π°Π½ΠΈΡΠΌ.
2. Π£ΡΠ΅Π±Π½ΠΈΠΊ ΠΏΠΎ Π΄ΠΈΡΡΠΈΠ»Π»ΡΡΠΈΠΈ Π·Π½Π°Π½ΠΈΠΉ ΠΎΡ PyTorch
Π ΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²ΠΎ ΠΎΡ PyTorch, ΠΊΠΎΡΠΎΡΠΎΠ΅ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ Π²Π²Π΅Π΄Π΅Π½ΠΈΠ΅ Π² ΡΠ΅Ρ Π½ΠΈΠΊΡ ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π·Π½Π°Π½ΠΈΠΉ Π΄Π»Ρ ΡΠ°Π·Π²ΡΡΡΡΠ²Π°Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π½Π° ΡΡΡΡΠΎΠΉΡΡΠ²Π°Ρ Ρ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΠΌΠΈ Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΠΌΠΈ ΡΠ΅ΡΡΡΡΠ°ΠΌΠΈ.
ΠΡΠ½ΠΎΠ²Π½ΡΠ΅ Π°ΡΠΏΠ΅ΠΊΡΡ ΡΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²Π°:
- ΠΠ·Π²Π»Π΅ΡΠ΅Π½ΠΈΠ΅ ΡΠΊΡΡΡΡΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΠΈΠΉ: Π Π³Π°ΠΉΠ΄Π΅ ΠΏΠΎΠΊΠ°Π·Π°Π½ΠΎ, ΠΊΠ°ΠΊ ΠΏΠΎΠ»ΡΡΠΈΡΡ ΠΏΡΠΎΠΌΠ΅ΠΆΡΡΠΎΡΠ½ΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΈΠ· ΠΎΠ±ΡΡΠ΅Π½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π΄Π»Ρ Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠ΅Π³ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ.
- ΠΠΎΠ΄ΠΈΡΠΈΠΊΠ°ΡΠΈΡ ΡΠΈΠΊΠ»ΠΎΠ² ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ Π² PyTorch: ΠΠ΄Π΅ΡΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΡ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ ΡΡΠ½ΠΊΡΠΈΠΉ Π² ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΡΠ΅ ΡΠΈΠΊΠ»Ρ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ Π΄Π»Ρ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π·Π½Π°Π½ΠΈΠΉ.
- ΠΠ° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°Π½ ΠΏΡΠΎΡΠ΅ΡΡ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ ΠΊΠΎΠΌΠΏΠ°ΠΊΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ, Ρ ΠΈΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΏΡΠ΅Π΄ΡΠΊΠ°Π·Π°Π½ΠΈΡ Π±ΠΎΠ»Π΅Π΅ ΡΠ»ΠΎΠΆΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠ°.
Π ΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΠΏΠΎΡΠ°Π³ΠΎΠ²ΡΠ΅ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΠΈ ΠΏΡΠΈΠΌΠ΅ΡΡ ΠΊΠΎΠ΄Π°, ΡΡΠΎ Π΄Π΅Π»Π°Π΅Ρ Π΅Π³ΠΎ ΡΠ΅Π½Π½ΡΠΌ ΡΠ΅ΡΡΡΡΠΎΠΌ, Π΅ΡΠ»ΠΈ Π²Ρ Ρ ΠΎΡΠΈΡΠ΅ Π½Π°ΡΡΠΈΡΡΡΡ ΠΎΠΏΡΠΈΠΌΠΈΠ·ΠΈΡΠΎΠ²Π°ΡΡ ΡΠ²ΠΎΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π΄Π»Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π² ΡΡΠ΅Π΄Π°Ρ Ρ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΠΌΠΈ ΡΠ΅ΡΡΡΡΠ°ΠΌΠΈ.
βͺΠ‘ΡΡΠ»ΠΊΠ°
3. Jetson Introduction to Knowledge Distillation ΠΎΡ Nvidia
Π Π΄Π°Π½Π½ΠΎΠΌ ΡΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²Π΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΏΡΠΎΡΠ΅ΡΡ ΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Π·Π½Π°Π½ΠΈΠΉ ΠΎΡ ΠΌΠΎΠ΄Π΅Π»ΠΈ OpenCLIP (vision-language model) ΠΊ ΠΌΠΎΠ΄Π΅Π»ΠΈ ResNet18 Π΄Π»Ρ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ Π½Π° Π½Π°Π±ΠΎΡΠ΅ Π΄Π°Π½Π½ΡΡ STL10.
ΠΡΠΎΠ±ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΡΠ΄Π΅Π»ΡΠ΅ΡΡΡ ΡΠΎΠΌΡ, ΠΊΠ°ΠΊ Π²ΡΠ±ΠΎΡ Π΄Π°Π½Π½ΡΡ , ΠΌΠ΅ΡΠΎΠ΄Ρ Π΄ΠΈΡΡΠΈΠ»Π»ΡΡΠΈΠΈ ΠΈ Π°ΡΡ ΠΈΡΠ΅ΠΊΡΡΡΠ° ΠΌΠΎΠ΄Π΅Π»ΠΈ, Π²Π»ΠΈΡΡΡ Π½Π° ΠΈΡΠΎΠ³ΠΎΠ²ΡΡ ΡΠΎΡΠ½ΠΎΡΡΡ.
ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, ΠΎΠ±ΡΡΠΆΠ΄Π°ΡΡΡΡ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΏΡΠΎΡΠΈΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π΄Π»Ρ ΠΈΡ ΡΠ°Π·Π²ΡΡΡΡΠ²Π°Π½ΠΈΡ Π½Π° ΡΡΡΡΠΎΠΉΡΡΠ²Π°Ρ NVIDIA Jetson Orin Nano.
4. Π£ΡΠ΅Π±Π½ΠΈΠΊ ΠΏΠΎ Π΄ΠΈΡΡΠΈΠ»Π»ΡΡΠΈΠΈ Π·Π½Π°Π½ΠΈΠΉ ΠΎΡ Keras
ΠΠΎΠ΄ΡΠΎΠ±Π½ΠΎ ΠΎΠΏΠΈΡΡΠ²Π°Π΅ΡΡΡ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΡ Π΄ΠΈΡΡΠΈΠ»Π»ΡΡΠΈΠΈ Π·Π½Π°Π½ΠΈΠΉ ΠΈ Π΅Π΅ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ Π² ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ.
5. Π ΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²ΠΎ ΠΏΠΎ Π΄ΠΈΡΡΠΈΠ»Π»ΡΡΠΈΠΈ ΠΎΡ
huggingface π€
ΠΠ΄Π΅ΡΡ ΠΏΠΎΠΊΠ°Π·Π°Π½ΠΎ, ΠΊΠ°ΠΊ Π²ΡΠΏΠΎΠ»Π½ΡΡΡ Π΄ΠΈΡΡΠΈΠ»Π»ΡΡΠΈΡ Π·Π½Π°Π½ΠΈΠΉ ΡΠ°Π³ Π·Π° ΡΠ°Π³ΠΎΠΌ Π½Π° ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠΌ ΠΏΡΠΈΠΌΠ΅ΡΠ΅.
6. ΠΠΈΡΡΠΈΠ»Π»ΡΡΠΈΡ Π·Π½Π°Π½ΠΈΠΉ Π΄Π»Ρ Π·Π°Π΄Π°Ρ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠ³ΠΎ Π·ΡΠ΅Π½ΠΈΡ ΠΎΡ huggingface
ΠΠ΄Π΅ΡΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ, ΠΊΠ°ΠΊ ΡΠ΄Π΅Π»Π°ΡΡ ΡΠ°ΠΉΠ½ΡΡΠ½ ViT-ΠΌΠΎΠ΄Π΅Π»ΠΈ Π² MobileNet Ρ ΠΏΠΎΠΌΠΎΡΡΡ API Trainer ΠΈΠ· Transformers.
#KnowledgeDistillation #Distillation #openai #keras #tutorial #course #freecourses #huggingface #Nvidia #pytorch
Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM