SDK vs. API: Which is Better for Building Your Face Recognition App? https://lnkd.in/e9NetkXg #facerecognition #facialrecognition #API #apidevelopment #appdevelopment #development #developers #ai #aiapplications #cloudsolutions #facedetection #security #securitysolutions #securityservices #securityintegration #imagerecognition #biometrics #biometricsecurity #deepfake #frauddetection #fraudprevention #fraud #python #securityintegration #sdk
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Laptop Price Predictor: Developed a Machine Learning based Streamlit application that predicts the appropriate price of laptops ?? ??based upon the configuration provided by the user.?????? Note: To view the app and complete project make sure to click on the links below ?? App: https://lnkd.in/det4VyDZ GitHub: https://lnkd.in/dHZkA7aK #machinelearning #app #streamlitshare #developers #mlengineers #datasciene #dataanalyst #dataenthusiast #python #eda #laptops #priceprediction #regressionmodel
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Pro Tip: If you're building a web app and need to share your hashtag#Machine Learning model, skip saving it to a file. Instead, create an hashtag#API! Why? An API: Eliminates environment and security headaches by avoiding dependency and version conflicts. Enables access from different languages and platforms-your model is just an HTTP request away! Simplifies integration with front-end frameworks, mobile apps, or other services. Ready to get started? Here's a quick guide on how to build an ML API with #FastAPI-get your model online in minutes! #WebDevelopment #APIDevelopment #ML #AI #TechTips #Python
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?? Pro Tip: If you're building a web app and need to share your #MachineLearning model, skip saving it to a file. Instead, create an #API! ?? Why? An API: ? Eliminates environment and security headaches by avoiding dependency and version conflicts. ? Enables access from different languages and platforms—your model is just an HTTP request away! ? Simplifies integration with front-end frameworks, mobile apps, or other services. Ready to get started? Here's a quick guide on how to build an ML API with #FastAPI—get your model online in minutes! ?? #WebDevelopment #APIDevelopment #ML #AI #TechTips #Python #AI
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https://lnkd.in/eSp8BP4k Try My Machine Learning App for Linear Regression: Here is the link to the App: https://lnkd.in/eXtNn7wg
Build a Linear Regression Machine Learning App with Streamlit and Python
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?? OCR Text Detection App GitHub: https://lnkd.in/dX8VBMX5 I'm excited to share my latest project, an OCR (Optical Character Recognition) app that helps users easily extract text from images. With this app, you can: ?? Capture or Choose an Image: Take a photo or select one from your gallery ?? Text Detection: Automatically detect and display words in the image ?? Text Display & Copy: View the detected text and copy it to the clipboard ??? Technologies Used: ?? Flutter: For the mobile interface ?? Flask: As the REST API server This project was developed from December to late January with a team of two, including SOUFIANE AIT TALB and me. It was a great experience working on this app, and I'm eager to hear any feedback or suggestions! #FlutterDev #Python #MobileAppDevelopment #OCR #ComputerVision #TechProjects #Flask #AppDevelopment
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?? Exciting News! ?? I’ve successfully implemented my CNN model in a mobile app, leveraging a Flask server for real-time image classification of Cat And Dog! ???? Here’s how it works: - The app sends an image to the Flask server via an API request. - The Flask server, a lightweight and powerful web framework in Python, handles the request, processes the image, and passes it through the CNN model. - The model then generates a prediction, which is sent back to the app as a response! ?? Flask’s simplicity and flexibility made it easy to deploy the model and integrate it with the app, making the entire process smooth and efficient. It’s been an amazing learning experience combining mobile development and AI. Stay tuned for more updates! ? #MobileApp #Flask #MachineLearning #CNN #DeepLearning #AI
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*Day 3 of" Building Your Own Al App" creating our own fully functional ChatBot Web App. Today, we took a deep dive into building our own Al application using open-source tools and Gemini. With step-by-step guidance, we integrated Al functionalities using Python. We harnessed Streamlit to create a sleek user interface and utilized Google Colab and VS Code for seamless development and collaboration. This journey has shown me that even complex Al projects are within reach with the right tools and support. A huge thanks to Dhana Vasanth for guiding us through the process and making it both accessible and enjoyable! and thanks to GUVI for making this hands-on learning experience. The journey of building our own Al-powered applications is becoming more exciting with each step. #GenerativeAl #BuildingAppUsingAl #ChatBot #LearnWithGUVI #GUVI #GUVIgeeksofficial
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I'm trying to get the order of script and function calls in a flask app. This application gets the Check it out: https://lnkd.in/dnS3CXeR Join the conversation! #profiler #python3x
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