I am new to ML and I am starting learning it. I am doing Joh Krohn course for Maths intro to ML. It is pretty clear explaind to me but I am struggling with one thing. In this task https://github.com/jonkrohn/ML-foundations/blob/master/notebooks/regression-in-pytorch.ipynb we used torch.optim.SGD torch SGD which was running thru all the example data.

I am trying to train a model for a specific task.
Here is a simple description:
image1
image2
Here are screenshots of two different datasets: The data in Image 1 is in the correct order, with no errors and no missing data. The data in Image 2, on the other hand, is disordered, contains noise, and has missing data.

everyone. i am trying to train yolov9 on some custom data on PyCharm instead of google colab as suggested by many tutorials i have watched. how do i do this?

I am currently working with the MERN stack (MongoDB, Express.js, React, Node.js) and am looking to expand my skills. I plan to start with Data Structures and Algorithms (DSA) in Java, but I also want to dive into Machine Learning. However, I am having trouble finding good resources for learning Machine Learning.

Máy in đang xài gặp các vấn đề không hoạt động tiếp được nữa do bị kẹt giấy phải làm sao đây????

I want to train a model to detect spam reviews. Not based on content of the message per se, bust stuff like frequency of messages of the user and other metadata. What do you think are the key data I need to feed the ai model

Here, i trying to build a Manhole object detection using cnn , In this model i got 95% accuracy and after training. im getting false positive like , if i test image with manhole(trained object) for detection it will draw the bounding box and i test a random image without trained object a random bounding box appears that is the problem , same in the live webcam testing but here if the object is not even detecting , getting some random bounding boxes in frame .Here i providing my code pls help