|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Tensorflow||179,058||327||78||6 hours ago||46||October 23, 2019||2,098||apache-2.0||C++|
|An Open Source Machine Learning Framework for Everyone|
|Transformers||116,020||64||2,452||6 hours ago||125||November 15, 2023||909||apache-2.0||Python|
|🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.|
|Pytorch||72,987||3,341||8,194||6 hours ago||39||November 15, 2023||13,255||other||Python|
|Tensors and Dynamic neural networks in Python with strong GPU acceleration|
|Cs Video Courses||61,557||17 days ago||2|
|List of Computer Science courses with video lectures.|
|Keras||59,808||680||9 hours ago||86||November 28, 2023||129||apache-2.0||Python|
|Deep Learning for humans|
|D2l Zh||51,074||1||1||6 days ago||51||August 18, 2023||59||apache-2.0||Python|
|Faceswap||47,636||6 days ago||19||gpl-3.0||Python|
|Deepfakes Software For All|
|Yolov5||43,512||11 hours ago||8||September 21, 2021||198||agpl-3.0||Python|
|YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite|
|Deepfacelab||43,455||a month ago||547||gpl-3.0||Python|
|DeepFaceLab is the leading software for creating deepfakes.|
|Tensorflow Examples||42,312||a year ago||218||other||Jupyter Notebook|
|TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)|
I have started 26 weeks of ML Code where you can learn Machine Learning in just 26 weeks . I will post the Schedule sooon that on which week you have to study which topic
While i don't want to overstate the complexity of the field, 30 days is awfully short.
One of the most easy pitfalls is to just take off-the-shelf implementations of algorithms and throw them against your problem. But most algorithms are based on assumptions and all of them have some limitations. A good grasp of basic statistics will help you:
Weird Data Stuff
Well, you didn't learn all this not to use it, right? Also, making sense of your results is important. And being critical for them as well. It is so easy to make a logical mistake which is not programming mistake. I.e., the software will run, but the result will be very wrong.
If you want to go all the way, take your results to a friend/family and try to explain high-level what you did, what the results are and what they mean. Again speaking from teaching experience, there are people who are really good at the technical stuff, but cannot transfer the relevant implications of it to a non-technical person.
Better to take any Online Course. then note down all course content and Prepare Schedule for 30 Days . i will Suggest you Best Online Machine Learning Course.
This course is fun and exciting, but at the same time we dive deep into Machine Learning. It is structured the following way:
Week 1 : Git Basics & Introduction to Python
Download infographic (https://bit.ly/2HH9JcG)
more to read (https://bit.ly/2HH9JcG)