TensorFlow CNN Tutorial: Flower Classification with Python 🌷

Hi, 🌼 In our latest video tutorial, we will dive into image classification using Python and TensorFlow. Discover how to create a Convolutional Neural Network (CNN) πŸ“Š that can identify various types of flowers 🌻. What you’ll learn: If you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras […]

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TensorFlow Image Classification Tutorial: ResNet50 vs. MobileNet

This is an image Classification tutorial using Python, TensorFlow, and Keras with Convolutional Neural Networks (CNNs). In this video, we’ll learn how to use pre-trained models to classify images based on Resnet50 and Mobilenet. If you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you

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TensorFlow Sports Image Classification : Building a Custom Model with TensorFlow and Keras

πŸŽ₯ In this video tutorial, we will dive deep into the world of sports image classification! πŸ€πŸ“Έ πŸ” What’s Covered in this Video: πŸ“¦ Dataset Download: We’ll start by obtaining a large sports image dataset from Kaggle, carefully curated with 21 unique sports categories. πŸ‹οΈβ€β™‚οΈ Model Building: Using TensorFlow and Keras, we’ll dive into the

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Food Recognition : Classifying 36 Fruits and Vegetables in TensorFlow

Hi, 🍏πŸ₯•πŸ… In this tutorial, we guide you through the process of building a neural network capable of classifying 36 different fruits and vegetables using TensorFlow and Python. πŸŽ₯ πŸ“š Here’s what you’ll learn: πŸ”Ή Data Preparation: Explore the dataset and learn how to preprocess and organize your image data effectively. πŸ”Ή Model Building: Construct

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🧠 Image Classification Tutorial: Train and Detect Objects with TensorFlow and Pixellib βš™οΈ

πŸŽ₯ Discover the world of image classification using TensorFlow, Pixellib, and Python in our latest video tutorial! 🌟 Learn how to train and detect custom images, enhancing your computer vision skills. πŸ“ΈπŸ” In this informative tutorial, we’ll explore the process of annotating objects within images, creating accurate labels with dot markings and JSON files. We’ll

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