| 1 - Introduction.mp4 | 4.2 MB | ||
| 10 - Introduction to Shiny Express for Python.mp4 | 23.6 MB | ||
| 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 | ||
| 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 | ||
| 2 - Input Sliders Text Output with Simple Server Logic.mp4 | 46.1 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 | ||
| 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 | ||
| 3 - Shiny Input Demo.mp4 | 77.4 MB | ||
| 30 - Understanding Indexing and Masking in Tensors.mp4 | 50 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 MB | ||
| 35 - Handson with More Broadcasting Examples.mp4 | 15.9 MB | ||
| 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 | ||
| 4 - Using HTML to Build a Multiplication Table in Shiny Part 1.mp4 | 16.5 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 | ||
| 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 | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 46 total files | |||
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.
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