Inception V3 Practical Implementation | Classify more than 500 Birds Species (!!!)
Автор: Eran Feit
Загружено: 2024-03-05
Просмотров: 1378
Описание:
Dive into the intricacies of Inception-v3 architecture, understanding its role as a neural network powerhouse in the realm of deep learning. Explore the nuances of Inception CNNs and their pivotal role in image classification tasks, alongside the practical implementation of Inception V3 for transfer learning. Unveil the secrets of GoogLeNet, a cornerstone in image classification, particularly in PyTorch implementations, as you dissect its architecture and witness its integration into the TensorFlow ecosystem. Delve into the GitHub repositories dedicated to image classification using Inception V3, where cutting-edge research meets practical application. Through TensorFlow's robust framework, explore the deployment of Inception-v3 models for transfer learning, revolutionizing image recognition paradigms in the realm of artificial intelligence.
Welcome to our tutorial on transfer learning using Inception V3 with TensorFlow!
We will classify 525 (!) Birds images
In this video, we'll guide you through the entire process of preparing your data, building the model, and testing its performance.
🔍 Data Preparation: We'll start by preparing and loading the train test and validation images.
🛠️ Model Building with TensorFlow Keras: Next, we'll dive into the implementation of Inception V3 architecture using TensorFlow's Keras API. You'll learn how to configure and fine-tune the pre-trained model for your specific task.
📊 Testing the Model: Once the model is trained, we'll show you how to test the model using a new and fresh image
You can download the code here : https://ko-fi.com/s/4090982a5a
Link for Medium post : / how-to-classify-525-bird-species-using-inc...
You can find more computer vision tutorials in my blog page : https://eranfeit.net/blog/
More relevant content in this playlist : • Best Image classification tutorials
~~~~~~~~~~~~~~~ recommended courses and books ~~~~~~~~~~~~~~~
If you’re just beginning, I recommend this step-by-step course designed to introduce you to the foundations of Computer Vision : https://trk.udemy.com/9LoE7E
If you’re already experienced and looking for more advanced techniques, check out this deep-dive course : https://trk.udemy.com/EEDyMD
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~~~~~~~~~~~~~~ Chapters ~~~~~~~~~~~~~
00:00 Introduction , Prepare the data
04:57 Build the Model - Transfer learning
18:48 Test The Model
~~~~~~~~~~~~~~ Credits ~~~~~~~~~~~~~
Music by Vincent Rubinetti
Download the music on Bandcamp: https://vincerubinetti.bandcamp.com/a...
Stream the music on Spotify: https://open.spotify.com/album/1dVyjw...
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