Web Applications from Scratch with Streamlit-0daytown

MP4 | Video: h264, 1280×720 | 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!

What you’ll learn:
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

Requirements
Python (or any programming language) basic knowledge

Description
Let’s build and publish Web Applications together from SCRATCH!

Sometimes 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 Sentiment 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 download (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!

Who this course is for
AI Professionals, Python Programmers, Machine Learning Students, Computer Science Students, IT Passionates

Web Applications from Scratch with Streamlit