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Applied Tags : Image Classification

  • Project - Building Cat vs Non-Cat Image Classifier using NumPy and ANN

    Topic
    11 Concepts | 2 Questions | 19 Assessments | 869 Learners

    Welcome to this project on the Numpy - Cat vs Non-cat Classifier with Logistic Regression using Numpy. In this project, you will use Python and Numpy to build a Logistic Regression Classifier from scratch, and apply it to predict the class of an input image - whether it is a cat or a non-cat.

    Though we have a lot of ready-made APIs like scikit-learn and Keras to build Machine Learning and Deep Learning models, it is very essential for a Machine Learning enthusiast to clearly understand the hidden mechanism behind the working of ML models. Upon completing this project, you will understand …

    Instructor: Vagdevi K
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    Project - Image Classification with Pre-trained Keras models

    Topic
    2 Concepts | 4 Assessments | 115 Learners

    Welcome to this project on Image Classification with Pre-trained Keras models. This project aims to impart the knowledge of how to access the pre-trained models(here we get pre-trained ResNet model) from Keras of TensorFlow 2, and appreciate its powerful classification capacity by making the model predict the class of an input image.

    Understanding the pre-trained models is very important because this forms the basis of transfer learning. one of the most appreciated techniques to perform the classification of a different task thus reducing the training time, the number of iterations, and resource consumption. Learning about the pre-trained models and …

    Instructor: Vagdevi K
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    Project - Introduction to Transfer Learning (Cat vs Non-cats Project)

    Topic
    14 Concepts | 2 Questions | 10 Assessments | 111 Learners

    Welcome to this project on Cat vs Non-cat Classifier using Transfer Learning. In this project, you will use Python and Keras to apply the Transfer Learning technique in order to build an image classifier, and apply it to predict the class of an input image - whether it is a cat or a non-cat.

    Deep Learning is computationally intensive, often demanding powerful computational resources to yield reasonable accuracies in the real world. The idea of Transfer Learning has become a boon for the computer vision and deep learning community as it has reduced the hunger of Deep Learning algorithms for powerful …

    Instructor: Vagdevi K