The Data Science and Python channel is for researchers and advanced programmers

Subscribe: t.me/DataScienceT

Create an Audiobook in Python

✅ More ♥️♥️ = more posts

@CodeProgrammer ♥️

Speech to Text using Python

✅ More ♥️♥️ = more posts

@CodeProgrammer ♥️

More ♥️👍 = more important projects

Building a Convolutional Neural Network in PyTorch

https://machinelearningmastery.com/building-a-convolutional-neural-network-in-pytorch/

✅ More ♥️♥️ = more posts

@CodeProgrammer ♥️

Don't Forget join to another channel
https://t.me/DataScienceT

How do Transformers work?

All the Transformer models mentioned above (GPT, BERT, BART, T5, etc.) have been trained as language models. This means they have been trained on large amounts of raw text in a self-supervised fashion. Self-supervised learning is a type of training in which the objective is automatically computed from the inputs of the model. That means that humans are not needed to label the data!

This type of model develops a statistical understanding of the language it has been trained on, but it’s not very useful for specific practical tasks. Because of this, the general pretrained model then goes through a process called transfer learning. During this process, the model is fine-tuned in a supervised way — that is, using human-annotated labels — on a given task

🔗 Read More

🌸 https://t.me/DataScienceT

Data Science With Python Workflow Cheat Sheet

Creator: business Science
Stars ⭐️: 75
Forked By: 38

https://github.com/business-science/cheatsheets/blob/master/Data_Science_With_Python_Workflow.pdf

https://t.me/DataScienceT