In this repo , I will dump all the code and notes and project, which I make while learning PyTorch
Studied the basics like Intro to Deep Learning, ML vs DL , introduction to PyTorch and its use in Fcailiating deep learning algorithms. And Did setup in Colab For PyTorch.
Practical-
- Intro To Tensors
- Creating Random Tensors
- Creating Tensors with Zeros And Ones in PyTorch
- Creating a Tensor Range and Tensors Like Other
Today , I concentrated more on tensors , and tried to understand the Data Types and some operations using PyTorch. Also had to enhance the setup, but finally moved to Google Colab-Research
Practical Topics Covered-
- Tensor - Data types, and manipulation
- Precision ( Comp. science)
- Creating random tensors
- Finding Out details about some tensors
- mathematical operations on tensors
- Creating tensor and addition
- multiplication
- substarction
- In-Built PyTorch Functions- add and multiply
Did a deep dive into Matrix concepts, and solved some theoretical questions for brush up and, then hands-on PyTorch code.
Practical-
- Element-wise & Matrix multiplication
- time comaprision of the "for loop" & "torch.matmul"
- different kind of errors like shape error etc.
- matrix transpose
link-https://github.com/kumaradityabtps/Learning-PyTorch-from-scratch/blob/main/PT_Day3.ipynb
After along break, resatarted studying pytorch and covered the more mathe mathtical and practical concepts.
Practical-
- Finding min, max, mean, sum etc.
- Reshaping, Stacking, Squeezing, and unsqueezing
- Indexing
- Finding positional min and max
Link-https://github.com/kumaradityabtps/Learning-PyTorch-from-scratch/blob/main/PT_Day4.ipynb
Today was more conceptual, then practicals. Studied the usability and applications ofthe ML concepts.
Practical-
- PyTorch tensors & Numpy
- Numpy array to tensor
- tensor to numpy array
- Reproducability
- Running Tensors and PyTorch objects on GPUs,
- Putting tensors (and models) on the GPU Link - https://github.com/kumaradityabtps/Learning-PyTorch-from-scratch/blob/main/PT_Day5.ipynb
Practical-
- test1
- test2
- test3
Practical-
- test1
- test2
- test3
Practical-
- test1
- test2
- test3