Data Dashboard GUI App with Taipy Scenarios - Step by Step Python Tutorial

In this video, we will create a beautiful Data Science Dashboard, that predicts the future values of stocks using different algorithms. We will start by designing a dynamic Graphic User Interface with an open source Python library named Taipy. Then, we will download S&P 500 stock exchange data that stores daily information all the way from year 2010. We will then plot the historic values of each stock, and use them to calculate a prediction for the next business day. The best part is, we will perform the predictions in parallel, using Taipy's Scenario Management Backend, and 3 different algorithms: Linear Regression, K Nearest Neighbors, and Recurrent Neural Network.

By the end of this video, you will gain the following skills and knowledge:
- get comfortable with designing full stack applications with Taipy.
- understand how to arrange time series data for training and prediction.
- learn how to plot graphs with plotly.
- learn how to quickly train and predict with Scikit-learn and Tensorflow.
- and of course, learn how to design, build and reason about advanced applications from scratch.

If you'd like to learn more or contribute to Taipy, checkout their:

💻 TUTORIAL CODE 💻
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⭐ WSL Installation Instructions (run line by line in Command Prompt):
wsl --run

⭐ Clone project GitHub repo:

⭐ Install cuDF Pandas [optional]:

⭐ Import Machine Learning Modules:

⭐ Copy Build RNN Function:
def build_RNN(n_features):
model = models.Sequential()
return model

🎥 RELATED VIDEOS 🎥
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⭐ Anaconda for beginners:
⭐ Simple Machine Learning GUI App with Taipy and Tensorflow:
⭐ Datetime Ultimate Guide:
⭐ If Name Equals Main:
⭐ List Comprehension:
⭐ Basic Guide to Pandas:
⭐ cuDF Pandas for beginners:

⏰ Time Stamps ⏰
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00:00 - intro
00:50 - environment setup and wireframe

GUI DESIGN - FRONT END
02:37 - images and text
03:57 - vertical group of elements (part block)
05:06 - date range selector
06:57 - horizontal group of elements (layout)
07:29 - dropdown selector

DATA LAYER
14:17 - download dataset from Kaggle
15:30 - install cuDF Pandas via GPU [optional]
18:10 - fill GUI placeholders with dataset values

TAIPY SCENARIOS - BACK END
21:08 - on change function
22:13 - add icons for dropdown elements
25:02 - basic Taipy scenarios logic (presentation)
25:44 - configure input and output data nodes
26:24 - configure task
27:28 - configure scenario
28:18 - initialize scenario orchestrator
29:12 - define function for scenario task
30:36 - write inputs, submit scenario and read outputs
41:20 - display graph with plotly
45:02 - display multiple functions in one graph
53:08 - on init function

MACHINE LEARNING
54:33 - split timeseries data into features and targets
01:00:26 - Linear Regression, KNN, RNN

🤝 Connect with me 🤝
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🔗 Github:
🔗 X:
🔗 LinkedIn:
🔗 Blog:
🔗 Discord:

💳 Credits 💳
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⭐ Beautiful titles, transitions, sound FX:
⭐ Icons and Graphics:

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[crisakab]

Hello. i watched this video and liked it a lot. nice studio, great project.i tried emulating the project but didn't workout so wanted to ask if this project supports intel(R) grahics. error message was invidia-smi not found. you really simplify python explanation. nice one. 👍

[ecsantana]

You are undoubtly born with the gift of Teaching... You not only simplify things, but makes anything so much fun to learn! ! !

[davidtindell]

Hi ! Thank You for providing this more 'advanced' and 'complete' Python Tutorial. Very engaging, helpful and useful !

[dagooka]

Thanks for the awesome tutorial! Keep up the great work!

[ayoubtorabi]

This video was absolutely amazing and informative. Thank you so much for your useful, practical, and up-to-date tutorials!.👍

[xyzxyz]

Awesome preparation for this flawless lesson. Congratulations for your pedagogical methods, Maria. Salutations from France.

[hklyt]

Missed you. You helped me so much in my CS degree. Graduated this year 🎉

[Juanca-yw]

Genial, ya active la notificación para que me avise 👏

[ersineser]

Thank you for great video and your time to teaching.

[Sinke_]

Like this Taipy thing, and you are killing it, Mariya 👍🏻

[paulinofm]

Hola 😀.
Amazing video!!, amazing project!!, amazing python packages!!! and super amazing teacher!!! 👧
SALUDOS DESDE ESPAÑA 🇪🇸

[hassanal]

As always, the teaching style is excellent all around! 🎓 I haven't completed watching the video, but I hope to finish it this weekend. 📅😊, Greate job Mariya 👏

[rentipollo]

great inspiration, happy to have found this channel

[GodX]

your voice is clear, well instruction, attraction, viral and lovely.

[EnterPlayMode]

Whoa ❤‍🔥 you got your own emojis? That’s tuff! 💪🏾🔥

[bakabaka]

Fan here, please keep sharing your knowledge

[DerFlotteReiter]

It would be amazing if you could make a video were you backtest the strategies.

And the tutorial is great. You present everything very well and your fluent speaking (without any "aaahhhs") is amazing.

[AndreCarneiro]

Amazing! I didn't know this lib. Thanks a lot!

[obc]

Nice tutorial, very instructive and easy to follow with your clear explanations. It must have consume a lot of your time. Thanks.

[themarksmith]

Just found and subbed to your channel - amazing stuff!