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      "body": "🍎🍌🍓 For CNN and deep learning enthusiasts! 🍊🍇🍍\n🚀 In this in-depth tutorial, we explain, step-by-step , the process of building a convolutional neural network (CNN) model tailored specifically for fruit classification. 🌱🍎\nThe process will describe the model training, choosing the rights layers and filters, training , and running a fresh test image to check our result.\nYou are welcome to subscribe for the channel and follow our next videos\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic\n\nBefore we continue , I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\nCheck out our tutorial here : https://youtu.be/sJoboLm8X-I\n\nThe code is in my Repo. I will leave a link in the video description.\n\nEnjoy\nEran\n\n#Python #Cnn #TensorFlow #deeplearning #deeplearning  #neuralnetworks #imageclassification #convolutionalneuralnetworks\n\n![Tensorflow fruits.jpg](https://cdn.steemitimages.com/DQmRbH6PVzLqE81UnC1ER1tsaPpkQ8WqBnM7S5Q8KYJfoDm/Tensorflow%20fruits.jpg)",
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      "body": "Step into the world of StyleGAN-Human, a cutting-edge AI technology that generates realistic human images. \nThis data-centric odyssey takes you on a journey through the power of machine learning and deep learning as it relates to human generation. \nFrom the creation of new faces to the manipulation of existing ones, this video explores the potential and limitations of this revolutionary technology. \nWhether you're a tech enthusiast, a data scientist, or just curious about the future of AI, don't miss this fascinating look into the world of StyleGAN-Human. \n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic.\nMoreover I recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\nWatch now and discover the potential of this AI technology! : https://youtu.be/RkZA7MhMdGQ\n\nEnjoy\nEran\n\n\n![human image generation.png](https://cdn.steemitimages.com/DQmTLiBqkzjfrkrA1NjRMt9kx9KJwdNBaVTepcQrrWBCYUQ/human%20image%20generation.png)\n#Python #styleGan #deeplearning #ai #computervision",
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      "body": "Step into the world of StyleGAN-Human, a cutting-edge AI technology that generates realistic human images. \nThis data-centric odyssey takes you on a journey through the power of machine learning and deep learning as it relates to human generation. \nFrom the creation of new faces to the manipulation of existing ones, this video explores the potential and limitations of this revolutionary technology. \nWhether you're a tech enthusiast, a data scientist, or just curious about the future of AI, don't miss this fascinating look into the world of StyleGAN-Human. \n\nWatch now and discover the potential of this AI technology! : https://youtu.be/RkZA7MhMdGQ\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic.\nMoreover I recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\nEnjoy\nEran\n\n\n![human image generation.png](https://cdn.steemitimages.com/DQmTLiBqkzjfrkrA1NjRMt9kx9KJwdNBaVTepcQrrWBCYUQ/human%20image%20generation.png)\n#Python #styleGan #deeplearning #ai #computervision",
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      "body": "Ever wondered how to clone your own voice using Python? In our latest tutorial, we walk you through the process of voice cloning with the TorToiSe library. \n\nYou'll learn how to clone your voice based on short and long audio files, and use the cloned voice to generate custom audio content like voiceovers for podcasts, audiobooks, and more. With Python and TorToiSe, you can create personalized voice assistants that sound just like you, or even generate realistic voiceovers for your own videos. \n\nSo if you're interested in exploring the exciting world of voice cloning, join us for this must-watch tutorial!\n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic\n\nMoreover I recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\nThe link for the video tutorial is here :   https://youtu.be/zrZ4efCkaxI\nI also shared the Python instructions to my Github repo in the video description.\n\n\nEnjoy\nEran\n\n#Python #TorToiSeLibrary #VoiceCloning #AudioContent #VoiceAssistants #Voiceovers #Tutorial\n\n![how to clone your own voice.png](https://cdn.steemitimages.com/DQmTh5eYmi4Sf46ZdgB1FBWa5CDaYyxqT2VWMeirNJ8XScD/how%20to%20clone%20your%20own%20voice.png)",
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      "body": "Do you remember playing \"Where's Wally?\" as a kid? \nWhat if you could take that game to the next level using advanced computer vision techniques?\nOur latest tutorial shows you how to find Wally in any image using Python and OpenCV. \nWe'll take an image of Wally and use it as a template to search for matches in larger images. \n\nThis involves using OpenCV functions and learning how to look for a specific image area based on another image.\n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\n\nBefore we continue, I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\ncheck out our video here: https://youtu.be/_iGmwb5petU\n\nYou can find the code in the video description.\n\nEnjoy,\nEran\n#Python #OpenCV #ObjectDetection #ImageProcessing #ComputerVision #Wally #WheresWaldo #ImageAnalysis #DeepLearning #MachineLearning\n\n![wally.png](https://cdn.steemitimages.com/DQmNqc7dh1RHFSWsa8jEELBRELcyRwqm5GNU9QtVdepqZG4/wally.png)",
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      "body": "Do you want to learn how to classify audio data using deep learning and TensorFlow Hub? \nCheck out our latest tutorial on Audio classification using deep learning and TensorFlow Hub! \nWe'll walk you through the entire process step-by-step, from setting up your environment to training and testing your audio classifier.\n\nTensorflow Hub has cool pre-trained models. \nImagine you have a audio file , and you would like to detect if it is a sound of a cat , or the sounds of water , or maybe to classify music …..\n\nSo, in this tutorial we will learn how to use this tensor hub model on your own audio files .\n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic\n\nBefore we continue, I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\nCheck out our tutorial here : https://youtu.be/_iX0VRp7UEA\n\nI also shared the Python instructions to my Github repo in the video description.\n\n\nEnjoy\nEran\n\n#Python #Cnn #TensorFlow #deeplearning #tensorflowhub #audioclassification, #deeplearning, #TensorFlowHub, #audioclassification #neuralnetworks\n\n![how to classify sound using tensor hub.png](https://cdn.steemitimages.com/DQmZ3gY9Xovbx1FCx8griw3iSF2UqtsGYjekVKxt9LJ14yy/how%20to%20classify%20sound%20using%20tensor%20hub.png)",
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      "body": "Learn how to perform image segmentation using Python OpenCV and contour detection in this step-by-step tutorial! \nDiscover how to convert images to grayscale, apply thresholding techniques, detect contours, and merge the detected contours with the original image for stunning effects. \nPerfect for beginners in computer vision, this tutorial will help you create amazing visual effects and gain skills that can be applied to a wide range of applications. \n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\n\nBefore we continue, I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n \n\nCheck out the tutorial: https://youtu.be/f6VgWTD_7kc\n \nEnjoy,\nEran Feit\n\n#ImageSegmentation #PythonOpenCV #ContourDetection #ComputerVision #TutorialForBeginners\n\n![Image-Segmentation-contours.png](https://cdn.steemitimages.com/DQmYNBjcqtySZLGYekRGmRPdpn8xCdJG8RPsQg27oDSUUQo/Image-Segmentation-contours.png)",
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      "body": "![Mobilenet.png](https://cdn.steemitimages.com/DQmQV9gTrFEBGt19QU12trFjJZ3UoRkmeT7HMunhW7Mwh5r/Mobilenet.png)\n\n\n\nLearn how to classify images with our new tutorial! \nIn this video, we'll show you how to use TensorFlow and Mobilenet to train an image classification model through transfer learning. \nWe'll guide you through the process of preprocessing image data, fine-tuning a pre-trained Mobilenet model, and evaluating its performance using validation data. \n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic\n\nMoreover, I recommend This graphics card: NVIDIA GeForce RTX 3060 Ti . I am using it to train my Tensorflow models.\nPerfect results and performance:   https://amzn.to/3mTa7HX\n\nThe link for the video tutorial is here : https://bit.ly/3owAuUX\nI also shared the Python code in the video description.\n\nEnjoy,\nEran\n\n#TensorFlow #Mobilenet #ImageClassification #TransferLearning #Python #DeepLearning #MachineLearning #ArtificialIntelligence #PretrainedModels #ImageRecognition #OpenCV #ComputerVision #Cnn",
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      "body": "Learn how to classify images with our new tutorial! \nIn this video, we'll show you how to use TensorFlow and Mobilenet to train an image classification model through transfer learning. \nWe'll guide you through the process of preprocessing image data, fine-tuning a pre-trained Mobilenet model, and evaluating its performance using validation data. \n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic\n\nMoreover, I recommend This graphics card: NVIDIA GeForce RTX 3060 Ti . I am using it to train my Tensorflow models.\nPerfect results and performance:   https://amzn.to/3mTa7HX\n\nThe link for the video tutorial is here : https://bit.ly/3owAuUX\nI also shared the Python code in the video description.\n\nEnjoy,\nEran\n\n#TensorFlow #Mobilenet #ImageClassification #TransferLearning #Python #DeepLearning #MachineLearning #ArtificialIntelligence #PretrainedModels #ImageRecognition #OpenCV #ComputerVision # Cnn\n\n\n![Mobilenet.png](https://cdn.steemitimages.com/DQmQV9gTrFEBGt19QU12trFjJZ3UoRkmeT7HMunhW7Mwh5r/Mobilenet.png)",
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      "body": "![How-to-detect-object-using-voice-yolo-tutorial.jpg](https://cdn.steemitimages.com/DQmbRTE6LnRZAyy8Bg2BUW5sGut8nbrMZDejsZjbQPpKRTF/How-to-detect-object-using-voice-yolo-tutorial.jpg)\n\nCheck out our latest video tutorial!\nIn this tutorial, we show you how to create a voice-controlled object detection system using the YOLO algorithm. \nBy combining object detection with speech recognition, you can create a system where you can say a word or phrase, and the system will detect the specified object in the camera frame and draw a rectangle around it.\n\nThis hands-on tutorial is perfect for anyone interested in learning about object detection, speech recognition, or just wants to build a cool project that combines the two. You'll learn about YOLO, how to set up the necessary libraries, how to train your model, and how to use voice commands to detect specific objects in real-time.\n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\n\nBefore we continue, I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\ncheck out our video here: https://youtu.be/fd1msoIpM5Q\n\nYou can find the code in the video description.\n\nEnjoy,\nEran\n\n#Python #OpenCV #ObjectDetection #ComputerVision #googlespeechrecognition #speechrecognition #Yolo",
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      "body": "![How-to-detect-object-using-voice-yolo-Demo.png](https://cdn.steemitimages.com/DQmTFb1ZGoaed69HKiWHskdu82ByTCQ5HWNvYYR813KMViw/How-to-detect-object-using-voice-yolo-Demo.png)\n\n\nCheck out our latest video tutorial!\nIn this tutorial, we show you how to create a voice-controlled object detection system using the YOLO algorithm. \nBy combining object detection with speech recognition, you can create a system where you can say a word or phrase, and the system will detect the specified object in the camera frame and draw a rectangle around it.\n\nThis hands-on tutorial is perfect for anyone interested in learning about object detection, speech recognition, or just wants to build a cool project that combines the two. You'll learn about YOLO, how to set up the necessary libraries, how to train your model, and how to use voice commands to detect specific objects in real-time.\n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\n\nBefore we continue, I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\ncheck out our video here: https://youtu.be/fd1msoIpM5Q\n\nYou can find the code in the video description.\n\nEnjoy,\nEran\n\n#Python #OpenCV #ObjectDetection #ComputerVision #googlespeechrecognition #speechrecognition #Yolo",
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      "body": "![cars-Resnet50.png](https://cdn.steemitimages.com/DQmTzgJyS6RnAA8PydxuWPrnoE6zX2Hj61iAF9S8fssmehp/cars-Resnet50.png)\n\nHi,\n\nIn this video tutorial, you'll discover how to classify car images using computer vision and deep learning.\nWe'll be using Tensorflow and Keras to configure a Resnet50 model that can quickly and accurately classify car brands with transfer learning. \nWhether you're interested in building your own image classification models or want to apply deep learning techniques to a variety of real-world problems, this tutorial is the perfect place to start !\n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic\n\nMoreover, I recommend This graphics card: NVIDIA GeForce RTX 3060 Ti . I am using it to train my Tensorflow models.\nPerfect results and performance:   https://amzn.to/3mTa7HX\n\nThe link for the video tutorial is here : https://bit.ly/3BJvKmK\nI also shared the Python code in the video description.\n\nEnjoy\n\nEran\n\n\n#Python #CNN #ComputerVision #DeepLearning #Tensorflow #Keras #Resnet50 #ImageClassification #TransferLearning #ConvolutionalNeuralNetwork #DataAugmentation #FineTuning #PythonLibraries #ObjectDetection #CarImages #CarBrands #MachineLearning #NeuralNetworks #ArtificialIntelligence #Programming #Tutorial #LearnComputerVision #TrainNeuralNetworks #ImageRecognition #ComputerScience #DataScience #SupervisedLearning #OpenSource #PythonProgramming #ImageProcessing #ClassifyingCars.",
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      "body": "Are you interested in learning how to use deep learning and image classification to predict chess pieces? \nCheck out our new tutorial on building a convolutional neural network model in Python with Tensorflow and Keras! \nThis step-by-step guide will show you how to build and train a model using CNN and evaluate its accuracy and loss\n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic\n\nMoreover, I recommend This graphics card: NVIDIA GeForce RTX 3060 Ti . I am using it to train my Tensorflow models.\nPerfect results and performance:   https://amzn.to/3mTa7HX\n\nThe link for the video tutorial is here : https://youtu.be/Y2MkEuZ3AEw\n\nI also shared the Python code in the video description.\n\nEnjoy\n\nEran\n\n#Python #Cnn #TensorFlow #AI #Deeplearning #CNN #MachineLearning #DeepLearning #ImageClassification #ComputerVision #VisualRecognition #NeuralNetworks",
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      "body": "Are you interested in learning how to use deep learning and image classification to predict chess pieces? \nCheck out our new tutorial on building a convolutional neural network model in Python with Tensorflow and Keras! \nThis step-by-step guide will show you how to build and train a model using CNN and evaluate its accuracy and loss\n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic\n\nMoreover, I recommend This graphics card: NVIDIA GeForce RTX 3060 Ti . I am using it to train my Tensorflow models.\nPerfect results and performance:   https://amzn.to/3mTa7HX\n\nThe link for the video tutorial is here : https://youtu.be/Y2MkEuZ3AEw\n\nI also shared the Python code in the video description.\n\nEnjoy\n\nEran\n\n#Python #Cnn #TensorFlow #AI #Deeplearning #CNN #MachineLearning #DeepLearning #ImageClassification #ComputerVision #VisualRecognition #NeuralNetworks",
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      "body": "Take your Python skills to the next level with this tutorial on using computer vision and OpenCV to play and control an Atari 2600 Grandprix game. \nWith this tutorial, you'll learn how to detect the cars in the game using OpenCV, control the car using keyboard commands, and create a self-driving car program that avoids obstacles. \nWhether you're a beginner or an experienced programmer, this tutorial will help you enhance your knowledge of computer vision, game development, and artificial intelligence. \n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\n\nPerfect course for every computer vision enthusiastic\n\nBefore we continue , I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\nYou can find the link for the tutorial here : https://youtu.be/e2EpH9SDSMs\nThe code is in the video description.\n\nEnjoy\nEran\n\n#Atari #python #opencv #computervision",
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      "body": "Take your Python skills to the next level with this tutorial on using computer vision and OpenCV to play and control an Atari 2600 Grandprix game. \nWith this tutorial, you'll learn how to detect the cars in the game using OpenCV, control the car using keyboard commands, and create a self-driving car program that avoids obstacles. \nWhether you're a beginner or an experienced programmer, this tutorial will help you enhance your knowledge of computer vision, game development, and artificial intelligence. \n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\n\nPerfect course for every computer vision enthusiastic\n\nBefore we continue , I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\nYou can find the link for the tutorial here : https://youtu.be/e2EpH9SDSMs\nThe code is in the video description.\n\nEnjoy\nEran",
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      "body": "Take your Python skills to the next level with this tutorial on using computer vision and OpenCV to play and control an Atari 2600 Grandprix game. \nWith this tutorial, you'll learn how to detect the cars in the game using OpenCV, control the car using keyboard commands, and create a self-driving car program that avoids obstacles. \nWhether you're a beginner or an experienced programmer, this tutorial will help you enhance your knowledge of computer vision, game development, and artificial intelligence. \n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\n\nPerfect course for every computer vision enthusiastic\n\nBefore we continue , I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N\n\nYou can find the link for the tutorial here : https://youtu.be/e2EpH9SDSMs\nThe code is in the video description.\n\nEnjoy\nEran",
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      "body": "Hi,\n\nIn this video tutorial, you'll discover how to classify car images using computer vision and deep learning.\nWe'll be using Tensorflow and Keras to configure a Resnet50 model that can quickly and accurately classify car brands with transfer learning. \nWhether you're interested in building your own image classification models or want to apply deep learning techniques to a variety of real-world problems, this tutorial is the perfect place to start !\n\nIf you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : http://bit.ly/3HeDy1V\nPerfect course for every computer vision enthusiastic\n\nThe link for the video tutorial is here : https://bit.ly/3BJvKmK\nI also shared the Python code in the video description.\n\nMoreover, I recommend This graphics card: NVIDIA GeForce RTX 3060 Ti . I am using it to train my Tensorflow models.\nPerfect results and performance:   https://amzn.to/3mTa7HX\n\nEnjoy\n\nEran\n\n\n#Python #CNN #ComputerVision #DeepLearning #Tensorflow #Keras #Resnet50 #ImageClassification #TransferLearning #ConvolutionalNeuralNetwork #DataAugmentation #FineTuning #PythonLibraries #ObjectDetection #CarImages #CarBrands #MachineLearning #NeuralNetworks #ArtificialIntelligence #Programming #Tutorial #LearnComputerVision #TrainNeuralNetworks #ImageRecognition #ComputerScience #DataScience #SupervisedLearning #OpenSource #PythonProgramming #ImageProcessing #ClassifyingCars.\n\n![cars-Resnet50.png](https://cdn.steemitimages.com/DQmTzgJyS6RnAA8PydxuWPrnoE6zX2Hj61iAF9S8fssmehp/cars-Resnet50.png)",
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