Interactive Data Science In Python With Shiny And Pytorch

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size2 GB
  • Uploaded Byfreecoursewb
  • Downloads12
  • Last checkedJun. 12th '25
  • Date uploadedJun. 12th '25
  • Seeders 2
  • Leechers14

Infohash : 43C39B68B28FEC1C974294CEA6F0C519C8D04258

Interactive Data Science In Python With Shiny And Pytorch

https://WebToolTip.com

Published 5/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.04 GB | Duration: 4h 4m

Learn to Build Interactive Data Science Apps Using Python, Shiny, Pandas, Seaborn, Matplotlib & PyTorch

What you'll learn
Build interactive web applications and dashboards using Shiny and Shiny Express in Python to visualize and explore data dynamically.
Master core Python data science libraries — Pandas, Seaborn, and Matplotlib — for effective data cleaning, analysis, and visualization.
Understand fundamental deep learning concepts and implement basic neural networks using PyTorch from scratch.
tch. Apply practical, hands-on techniques to create real-world data-driven projects that combine interactivity with machine learning insights.

Requirements
Basic understanding of Python programming (variables, functions, loops).
No prior experience with Shiny, data visualization libraries, or PyTorch is required — everything is taught from scratch.
A computer with Python installed
Curiosity and willingness to learn interactive data science and pytorch fundamentals.

Files:

[ WebToolTip.com ] Interactive Data Science In Python With Shiny And Pytorch
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1 - Introduction
    • 1 - Introduction.mp4 (4.2 MB)
    2 - Data Visualization and Shiny
    • 10 - Introduction to Shiny Express for Python.mp4 (23.6 MB)
    • 2 - Input Sliders Text Output with Simple Server Logic.mp4 (46.1 MB)
    • 3 - Shiny Input Demo.mp4 (77.4 MB)
    • 4 - Using HTML to Build a Multiplication Table in Shiny Part 1.mp4 (16.5 MB)
    • 5 - Using HTML to Build a Multiplication Table in Shiny Part 2.mp4 (40.9 MB)
    • 6 - Using Shiny in VSCode and Deploying Your App.mp4 (130.8 MB)
    • 7 - Exploring Shiny Components.mp4 (166.2 MB)
    • 8 - Working with Action Buttons and Checkboxes.mp4 (49.1 MB)
    • 9 - Using Checkbox Groups Selectize and RowColumn Structures.mp4 (60.1 MB)
    3 - Using Official Shiny Demos as a Learning Tool
    • 11 - Using Official Shiny Demos as a Learning Tool Sidebar App.mp4 (112.9 MB)
    • 12 - Walkthrough Shinys KDE Plot Demo Project.mp4 (6.5 MB)
    • 13 - Walkthrough Penguins Dashboard Demo by the Shiny Team.mp4 (53.5 MB)
    4 - Building an Interactive CSV Data Dashboard in Shiny for Python
    • 14 - Project Setup.mp4 (37.4 MB)
    • 15 - Adding the Imports.mp4 (9.4 MB)
    • 16 - Uploading a CSV File.mp4 (27.5 MB)
    • 17 - DASH-4-Displaying-Quick-Stats.mp4 (330.3 MB)
    • 17 - Displaying Quick Stats.mp4 (21.8 MB)
    • 18 - Dynamic Column Picker for CSV Data.mp4 (18.2 MB)
    • 19 - Displaying Column Details in an Info Card.mp4 (43.5 MB)
    • 20 - Visualizing Numeric Columns with Histograms.mp4 (37.1 MB)
    • 21 - Visualizing Categorical Columns with Pie or Bar Charts.mp4 (12.6 MB)
    • 22 - Conditional Pie or Bar Charts and NoData Messaging.mp4 (28.5 MB)
    5 - PyTorch Fundamentals
    • 23 - Google Colab and tqdm.mp4 (61.5 MB)
    • 24 - How to Get Help with PyTorch.mp4 (51.6 MB)
    • 25 - Exploring Additional Help Resources.mp4 (17.4 MB)
    • 26 - Introduction to PyTorch and Tensors Part 1.mp4 (37.2 MB)
    • 27 - Introduction to PyTorch and Tensors Part 2.mp4 (29.2 MB)
    • 28 - Leveraging the GPU for PyTorch in Google Colab.mp4 (7.6 MB)
    • 29 - Understanding Mathematical Operations on Tensors.mp4 (95.3 MB)
    • 30 - Understanding Indexing and Masking in Tensors.mp4 (50.0 MB)
    • 31 - Expanding on Masking in PyTorch.mp4 (73.3 MB)
    • 32 - Cloning Tensors for Safe Operations.mp4 (10.4 MB)
    • 33 - Broadcasting in PyTorch The First Steps.mp4 (17.3 MB)
    • 34 - Broadcasting Next Steps.mp4 (27.0 MB)
    • 35 - Handson with More Broadcasting Examples.mp4 (15.9 MB)
    6 - Torch Sight PyTorch Image Classification using Python and Shiny
    • 36 - Getting Started with TorchSight.mp4 (39.7 MB)
    • 37 - Adding the PyTorch and Image Processing Imports.mp4 (26.4 MB)
    • 38 - Importing the TorchVision Models.mp4 (12.8 MB)
    • 39 - Implementing the Get Model Function.mp4 (28.1 MB)
    • 40 - Image Transformations.mp4 (26.1 MB)
    • 41 - Creating the Title and Sidebar.mp4 (32.6 MB)
    • 42 - Getting the ImageNet Labels and Prompting the User for Images.mp4 (38.4 MB)
    • 43 - PyTorch Inference.mp4 (37.5 MB)
    • Bonus Resources.txt (0.1 KB)

Code:

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