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PyTorch for Deep Learning Computer Vision Bootcamp 2024

سرفصل های دوره

Master Computer Vision in PyTorch/Python: Beginner to Pro with Expert Tips on Convolutional Neural Networks (CNNs)


1 - Welcome Aboard
  • 1 - Why PyTorch is Powerful

  • 2 - Introduction
  • 2 - Introduction to Pytorch
  • 3 - Getting System Ready
  • 4 - Create Tensors in Pytorch
  • 5 - Tensor Slicing and Reshape
  • 6 - Mathematical Operations on Tensors
  • 7 - Numpy in Pytorch
  • 8 - What is CUDA
  • 9 - Pytorch on GPU
  • 10 - Download Materials.html
  • 10 - Section-Intro-To-Pytorch.zip

  • 3 - AutoGrad in Pytorch
  • 11 - Autograd in Pytorch
  • 12 - Implementing Gradient Descent using Autograd
  • 13 - Download Materials.html
  • 13 - Pytorch-AutoGrad.zip

  • 4 - Creating Deep Neural Networks in Pytorch
  • 14 - Building first neural network
  • 15 - Writing Deep neural network
  • 16 - Writing Custom NN module
  • 17 - Download Materials.html
  • 17 - Writing-Deep-NN-pytorch.zip

  • 5 - CNN on Pytorch
  • 18 - Data Loading CIFAR10
  • 19 - Data Visualization
  • 20 - CNN Recap
  • 21 - First CNN
  • 22 - CNN Deep layers
  • 23 - CNN-CIFAR10-Part-1.zip
  • 23 - Download Materials.html

  • 6 - LeNet Architecture in Pytorch
  • 24 - LeNet Overview
  • 25 - LeNet Model in Pytorch
  • 26 - Preparation Evaluation
  • 27 - CNN-CIFAR10-Part-2.zip
  • 27 - Download Materials.html

  • 7 - Optional Learning Python Basics
  • 28 - Why Computer Programming Language
  • 29 - Why Python
  • 30 - Getting System Ready Installing Jupyter Notebook
  • 31 - Jupyter Notebook Tips Tricks
  • 32 - What is Covered in this section
  • 33 - Variables in Python
  • 34 - Print Function
  • 35 - Numeric Data Type
  • 36 - String Data Type
  • 37 - Boolean Data Type
  • 38 - Type Conversion Type Casting
  • 39 - Adding Comments in Python Programming Language
  • 40 - Data Structures in Python
  • 41 - Tuples Sets in Python
  • 42 - Python Dictionaries
  • 43 - Conditional Statements in Python if
  • 44 - Conditional Statements in Python While
  • 45 - Inbuilt Functions in Python range input
  • 46 - For Loops
  • 47 - Functions in Python
  • 48 - Classes in Python

  • 8 - Mini Project with Python Basics
  • 49 - DLAI-S05-Mini-Project-Hangman.zip
  • 49 - Section Attachment.html
  • 50 - Mini Project Hangman
  • 51 - Writing a class
  • 52 - Mini Project Continued
  • 53 - Logic Building
  • 54 - Logic for Single Letter input
  • 55 - Final Testing

  • 9 - Python for Data Science Numpy
  • 56 - Numpy Library Code.html
  • 56 - dlai-s07a02-to-a06-numpy.zip
  • 57 - Why Numpy.html
  • 58 - Numpy
  • 59 - Resize Reshape of Arrays
  • 60 - Slicing
  • 61 - Broadcasting
  • 62 - Mathematical Operations Functions in Numpy

  • 10 - Python for Data Science Pandas
  • 63 - Pandas-Attachment.zip
  • 63 - Section Attachments.html
  • 64 - Pandas Library
  • 65 - Pandas Dataframe
  • 66 - Pandas Dataframe Load from External file
  • 67 - Working with null values
  • 68 - Slicing Pandas Dataframe
  • 69 - Imputation

  • 11 - Python for DataScience Matplotlib
  • 70 - Section Attachments.html
  • 70 - dlai-s09-matplotlib.zip
  • 71 - Matplotlib Introduction
  • 72 - Format the plot
  • 73 - Plot Formatting Scatter Plot
  • 74 - Histplot

  • 12 - Additional Concepts from Machine Learning
  • 75 - Bonus How do you select a Model in ML
  • 76 - Bonus Get More from Learning Journey.html

  • 13 - Machine Learning for Projects
  • 77 - Understanding Generative AI
  • 78 - Machine learning Deployment Part 1 Model Prep End to End
  • 79 - Machine learning Deployment Part 2 Deploy Flask App End to End
  • 80 - Streamlit Tutorial
  • 81 - Bonus Content References.html
  • 82 - Packaging the ML Models
  • 83 - Docker Containers for Data Science and ML Projects
  • 84 - Course Trailer on MLOps
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    تولید کننده:
    شناسه: 39123
    حجم: 6956 مگابایت
    مدت زمان: 701 دقیقه
    تاریخ انتشار: ۱۱ مرداد ۱۴۰۳
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