Train & Deploy TFLite Object Detection for Android (2025)

Partner: Udemy
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Description: Mobile AI is shifting from cloud to on-device. With TensorFlow Lite (TFLite) you can run real-time object detection directly on Android phones—no server, zero latency. This course gives you an end-to-end workflow to train, convert, and deploy custom models using Kotlin and Java.What You’ll MasterData Collection & AnnotationCapture images and label them with LabelImg, CVAT, or Roboflow to create high-quality datasets.Model Training in TensorFlow / YOLO / EfficientDet / SSD-MobileNetHands-on Colab notebooks show you how to train from scratch or fine-tune pre-trained weights.TFLite Conversion & OptimizationQuantize, prune, and add metadata for maximum FPS and minimum battery drain.Android Integration (CameraX + ML Model Binding)Build apps in Kotlin or Java that detect objects in both images and live camera streams.Using Pre-Trained ModelsPlug in ready-made YOLOv8-Nano, EfficientDet-Lite, or SSD-MobileNet with just a few lines of code.Included ResourcesProduction-ready Android templates (Kotlin & Java) worth $1,000+Re-usable model-conversion scripts and Colab notebooksPre-annotated sample dataset to get you started fastCheatsheets for common TFLite errors and performance tuningReal-World Use-Cases You’ll BuildSmart CCTV with intrusion alertsIndustrial defect detection on assembly linesCrowd counting & retail analytics dashboardsPrototype modules for self-driving or AR appsWho Should Enroll?<stron
Category: Development > Mobile Development > Android Development
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Price: 19.99
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Source: Impact
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