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Web Applications from Scratch with Streamlit

LeeAndro

Trusted Editor
Trusted Editor
Web Applications from Scratch with Streamlit
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 15 lectures (6h 46m) | Size: 4.15 GB

Build and Deploy your Web Apps from Scratch with the incredible Streamlit!


Seat with me and start CODING TOGETHER!

Building complete Web Applications from Scratch using Streamlit

Deploying your Web Applications on Streamlit Share

Getting Strong Skills about ALL Streamlit's Basic and Advanced Features

Managing NLP, Imaging, Data Base and Hashing Packages in Streamlit

Python (or any programming language) basic knowledge

Let's build and publish Web Applications together from SCRATCH!

Somes the best way to learn is not study tons of pages but start doing things together with experts. In this course you are invited to seat together with me coding and making Web Apps step-by-step, instruction after instruction.

Building and Deploying simple and more advanced Web Applications from Scratch using Streamlit is the best way to acquire all the SKILLS needed to create any kind of web application as complex and as big as you want. With this approach you will move from zero to hero in a real blink of an eye!

In this lessons we see how to build up a simple NLP Web App and a simple tool for Covid-19 Detection leveraging the incredible framework named Streamlit and using packages such as Gensim (for Summary), Text Blob (for Language Detection, Translation and Sennt Analisys), Spacy (for Tokens and Lemmas), Neat Text (for Text Cleaning), WordCloud (for WordCloud Plotting), Tensorflow (for Predictions/Classification), Pillow (for Images), Open-CV (for Images Enhancement), etc.

Once our Web Apps are completed and Tested we publish them online using Streamlit's Share Service (for this task is required a Github account).

In the Advanced Techniques Part we learn how detect automatically the file type when we use file_uploader in our applications, how to create in our web apps an advanced Login/Signup area (that makes the hashing of the password to guarantee data safety, then stores username and password on a data base) and all the tricks to deal with Models and Corpus (for Spacy and TextBlob) when we want to deploy our web applications to Streamlit Share.

As First BONUS Lesson a CRASH COURSE about Streamlit basic features.

As Second BONUS Lesson a COURSE about Python Coding Environment Setup.

Don't hesitate to contact me for any kind of question!

CHEERS!

AI Professionals, Python Programmers, Machine Learning Students, Computer Science Students, IT Passionates



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