How To Actually Use MobileNetV3 for Fish Classifier
This is a transfer learning tutorial for image classification using TensorFlow involves leveraging pre-trained model MobileNet-V3 to enhance the accuracy of image classification tasks. By employing transfer learning with MobileNet-V3 in TensorFlow, image classification models can achieve improved performance with reduced training time and computational resources. You can download the dataset here : https://www.kaggle.com/datasets/crowww/a-large-scale-fish-dataset You can download the code here : https://ko-fi.com/s/4d8e51bca8 You can find more computer vision tutorials in my blog page : https://eranfeit.net/blog/ More relevant content in this playlist : https://www.youtube.com/playlist?list=PLdkryDe59y4aCcCN4ioFpdLVAGZ_dFeFr ~~~~~~~~~~~~~~~ recommended courses and books ~~~~~~~~~~~~~~~ A perfect course for learning modern Computer Vision with deep dive in TensorFlow , Keras and Pytorch . You can find it here : http://bit.ly/3HeDy1V I also recommend this book, https://amzn.to/44GnlLW : "Make Your Own Neural Network - An In-depth Visual Introduction For Beginners ". ~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~ ☕ Buy me a coffee - https://ko-fi.com/eranfeit 🖥️ Email : [email protected] 🌐 https://eranfeit.net 🤝 Fiverr : https://www.fiverr.com/s/mB3Pbb 🐦 Twitter - https://twitter.com/eran_feit 📸 Instagram - https://www.instagram.com/eran_feit/ ▶️ Subscribe - youtube.com/@eranfeit?sub_confirmation=1 🐙 Facebook - https://www.facebook.com/groups/3080601358933585 📝 Medium - https://medium.com/@feitgemel ~~~~~~~~~~~~~~ SUPPORT ME 🙏~~~~~~~~~~~~~~ 🅿 Patreon - https://www.patreon.com/EranFeit ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #EranFeit #MobilenetV2 #python Chapters : 00:00 Introduction 00:39 Data preparation 12:53 Build the model (Transfer learning) 20:02Test the model ~~~~~~~~~~~~~~ Credits ~~~~~~~~~~~~~ Music by Vincent Rubinetti Download the music on Bandcamp: https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown Stream the music on Spotify: https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u
This is a transfer learning tutorial for image classification using TensorFlow involves leveraging pre-trained model MobileNet-V3 to enhance the accuracy of image classification tasks. By employing transfer learning with MobileNet-V3 in TensorFlow, image classification models can achieve improved performance with reduced training time and computational resources. You can download the dataset here : https://www.kaggle.com/datasets/crowww/a-large-scale-fish-dataset You can download the code here : https://ko-fi.com/s/4d8e51bca8 You can find more computer vision tutorials in my blog page : https://eranfeit.net/blog/ More relevant content in this playlist : https://www.youtube.com/playlist?list=PLdkryDe59y4aCcCN4ioFpdLVAGZ_dFeFr ~~~~~~~~~~~~~~~ recommended courses and books ~~~~~~~~~~~~~~~ A perfect course for learning modern Computer Vision with deep dive in TensorFlow , Keras and Pytorch . You can find it here : http://bit.ly/3HeDy1V I also recommend this book, https://amzn.to/44GnlLW : "Make Your Own Neural Network - An In-depth Visual Introduction For Beginners ". ~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~ ☕ Buy me a coffee - https://ko-fi.com/eranfeit 🖥️ Email : [email protected] 🌐 https://eranfeit.net 🤝 Fiverr : https://www.fiverr.com/s/mB3Pbb 🐦 Twitter - https://twitter.com/eran_feit 📸 Instagram - https://www.instagram.com/eran_feit/ ▶️ Subscribe - youtube.com/@eranfeit?sub_confirmation=1 🐙 Facebook - https://www.facebook.com/groups/3080601358933585 📝 Medium - https://medium.com/@feitgemel ~~~~~~~~~~~~~~ SUPPORT ME 🙏~~~~~~~~~~~~~~ 🅿 Patreon - https://www.patreon.com/EranFeit ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #EranFeit #MobilenetV2 #python Chapters : 00:00 Introduction 00:39 Data preparation 12:53 Build the model (Transfer learning) 20:02Test the model ~~~~~~~~~~~~~~ Credits ~~~~~~~~~~~~~ Music by Vincent Rubinetti Download the music on Bandcamp: https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown Stream the music on Spotify: https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u