Streamlit: To build the interactive web app. Folium: For creating dynamic, interactive maps. Pandas & NumPy: For data manipulation and analysis. Fuzzy Matching (via FuzzyWuzzy): To handle similar keywords and standardize terms. (P.S. This entire project was built in just three weeks. So pleas...
Build and Learn: AI App Development for Beginners: Unleashing ChatGPT API with LangChain & Streamlit Generative AI in Healthcare - The ChatGPT Revolution Generative AI in Accounting Guide: Explore the possibilities of generative AI in accounting Using Generative AI in Business Whitepaper Generative ...
For requirements and the Streamlit Python code, see the the GitHub repository. Benchmarking Results Let's compare the outputs from directly asking the LLM vs using RAG with LLM. The LLM originally gives the following response: Diabetes is a serious health problem in Africa, where it affects ...
Streamlit makes it easy to create and share beautiful, custom web apps for machine learning and data science. In just a few minutes we can build and deploy powerful data apps. Trending Bot Articles: 1. How Conversational AI can Automate Customer Service 2. Automated vs Live Chats: What will...
Join my Newsletter Subscribe Now Adil Moujahid Support me on Ko-fi Follow @AdilMouja Published Mon 15 June 2020 ←Home Analyzing Messi and Ronaldo's Games using Python and Streamlit// tags python streamlit
Visualizations with Altair Spelling Corrector Program in Python Spelling Checker Program in Python Streamlit Tutorial: How to Deploy Streamlit Apps on RStudio Connect Full list of contributing R-bloggers Archives Archives Other sites Jobs for R-users SAS blogsCopyright...
Deep Learning MediaPipe Pose Estimation Streamlit This article aims to build an AI fitness trainer that can help you perform squats seamlessly, irrespective of whether you are a beginner or a pro. To achieve this task, we can harness the power of a deep learning based human pose estimation ...
In the last few years there have been more attempts at a fresh approach to statistical timeseries forecasting using the increasingly accessible tools of machine learning. This means methods like neural networks and extreme gradient boosting, as supple...
This can be achieved using a single line of code in the seaborn library. In the arguments we can pass in the workingdf dataframe for data, and the WELL column for the hue. The latter of which will split the data up into individual boxes, each with it’s own unique color. ...
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