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Rismon Hasiholan
Step By Step Tutorials on Deep Learning Using Scikit-Learn, Keras, and TensorFlow with Python GUI
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749130Step By Step Tutorials on Deep Learning Using Scikit-Learn, Keras, and TensorFlow with Python GUIhttps://www.gandhi.com.mx/step-by-step-tutorials-on-deep-learning-using-scikit-learn-keras-and-tensorflow-with-python-gui-1/phttps://gandhi.vtexassets.com/arquivos/ids/1049832/b1f9c5fe-86c3-4c6a-af06-8a5aa0674bd2.jpg?v=638337269217330000226226MXNBALIGE PUBLISHINGInStock/Ebooks/747519Step By Step Tutorials on Deep Learning Using Scikit-Learn, Keras, and TensorFlow with Python GUI226226https://www.gandhi.com.mx/step-by-step-tutorials-on-deep-learning-using-scikit-learn-keras-and-tensorflow-with-python-gui-1/phttps://gandhi.vtexassets.com/arquivos/ids/1049832/b1f9c5fe-86c3-4c6a-af06-8a5aa0674bd2.jpg?v=638337269217330000InStockMXN99999DIEbook20211230004756613_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1230004756613_<p>In this book, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to implement deep learning on classifying fruits, classifying cats/dogs, detecting furnitures, and classifying fashion.</p><p>In Chapter 1, you will learn to create GUI applications to display line graph using PyQt. You will also learn how to display image and its histogram. Then, you will learn how to use OpenCV, NumPy, and other libraries to perform feature extraction with Python GUI (PyQt). The feature detection techniques used in this chapter are Harris Corner Detection, Shi-Tomasi Corner Detector, and Scale-Invariant Feature Transform (SIFT).</p><p>In Chapter 2, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform classifying fruits using Fruits 360 dataset provided by Kaggle (https://www.kaggle.com/moltean/fruits/code) using Transfer Learning and CNN models. You will build a GUI application for this purpose.</p><p>In Chapter 3, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform classifying cats/dogs using dataset provided by Kaggle (https://www.kaggle.com/chetankv/dogs-cats-images) using Using CNN with Data Generator. You will build a GUI application for this purpose.</p><p>In Chapter 4, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform detecting furnitures using Furniture Detector dataset provided by Kaggle (https://www.kaggle.com/akkithetechie/furniture-detector) using VGG16 model. You will build a GUI application for this purpose.</p><p>In Chapter 5, you will learn how to use TensorFlow, Keras, Scikit-Learn, OpenCV, Pandas, NumPy and other libraries to perform classifying fashion using Fashion MNIST dataset provided by Kaggle (https://www.kaggle.com/zalando-research/fashionmnist/code) using CNN model. You will build a GUI application for this purpose.</p>1230004756613_BALIGE PUBLISHINGlibro_electonico_6a5695cf-f597-37af-83df-2807edc837af_1230004756613;1230004756613_1230004756613Rismon HasiholanInglésMéxicohttps://getbook.kobo.com/koboid-prod-public/f2ca928b-958d-498f-bb70-f76c6615d8f6-epub-e25b720b-fc3a-403a-8bfe-e75d07dbb045.epub2021-05-03T00:00:00+00:00BALIGE PUBLISHING