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 …
Welcome to this project on Image Classification with Pre-trained InceptionV3 Network. This project aims to impart the knowledge of how to access the pre-trained models(here we get pre-trained Inception 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 …
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Welcome to the project on Building a Neural Network for Image Classification with TensorFlow. In this project, we would learn how to develop a neural network classifier from very scratch, using TensorFlow 2.
We would build and train a dense neural network on the Fashion MNIST dataset and evaluate its performance with some test samples. This project aims to impart the knowledge of the basic steps involved in building a neural network, working with TensorFlow 2, training a neural network, and make the learner comfortable with the cutting-edge technology - TensorFlow 2.
Skills you will develop:
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 …
Welcome to this project on Deploy Image Classification Pre-trained Keras model using Flask. In this project, we will have a comprehensive understanding of how to deploy a deep learning model as a web application using the Flask framework.
Developing a machine learning or deep learning model is very important to solve problems using AI. On the other hand, it is equally important to have a knowledge of how to deploy those amazing problem-solving models into such an interface which enables the users to make use of these solutions. Even many apps we use today, like YouTube, Amazon/Flipkart shopping, FaceApps …
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 …
Welcome to the project on Hosting an Image Classification App on Heroku. In this project, we will get a basic understanding of how to deploy a web app on Heroku, a Platform as a Service.
Heroku is a cloud platform for the deployment and management purposes of web applications. It could be considered as one of the best solutions for hosting web-apps very quickly, thus allowing the developer to concentrate more on development.
Welcome to this project on Deploy Image Classification Pre-trained Keras model using Flask. In this project, we will have a comprehensive understanding of how to deploy a deep learning model as a web application using the Flask framework.
Developing a machine learning or deep learning model is very important to solve problems using AI. On the other hand, it is equally important to have a knowledge of how to deploy those amazing problem-solving models into such an interface that enables the users to make use of these solutions. Even many apps we use today, like YouTube, Amazon/Flipkart shopping, FaceApps …