How to classify digits using a LaNet in Keras and Python Classifying digits using a LeNet in Keras and Python is a straightforward process that involves several steps. In this essay, we will discuss these steps in detail. The first step is to prepare the data for the model. This typically involves loading …
How to build a LaNet using Keras and Python LeNet is a convolutional neural network architecture designed to recognize handwritten digits. It was developed by Yann LeCun in the late 1990s and is considered a pioneer in the field of deep learning. In this essay, we will discuss how to build a LeNet …
How to save a deep learning model: A simple CNN model in Python for Image Classification Saving a deep learning model is an important step to ensure that the model can be used later on without having to retrain it from scratch. In this essay, we will discuss how to save a simple …
In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in Python programming: Learn_By_Example_Image_Augmentation_Part_1. What should I learn from this recipe? You will learn: How to code a keras and tensorflow model in Python. How to setup a sequential …
How to classify images using CNN layers in Keras: An application of MNIST Dataset Convolutional Neural Networks (CNNs) are a powerful tool for image classification tasks. They work by learning hierarchical representations of the image, where each layer captures a different level of abstraction. In this essay, we will discuss how to classify images …
How to setup CNN layers in Keras for image classification Convolutional Neural Networks (CNNs) are a type of deep learning model that are particularly well-suited for image classification tasks. CNNs are designed to process data that has a grid-like topology, such as an image. They work by learning hierarchical representations of the image, …
How to predict cancer (cancer data) using a keras deep learning model Predicting cancer using a keras deep learning model is a process that involves several steps. The cancer dataset is a popular dataset for classification tasks, and it consists of various features such as cell size, cell shape, and bare nuclei, among …
How to predict wine-class (wine data) using a keras deep learning model Predicting the class of a wine using a keras deep learning model is a process that involves several steps. The wine dataset is a popular dataset for classification tasks, and it consists of various features such as alcohol content, acidity, and …
How to predict diabetes (diabetes data) using a keras deep learning model Predicting diabetes using a keras deep learning model is a process that involves several steps. The diabetes dataset is a popular dataset for classification tasks, and it consists of various features such as age, blood pressure, BMI, diabetes pedigree function and a …
How to classify Flowers (iris data) using a keras deep learning model Classifying flowers, specifically the iris data, using a keras deep learning model is a process that involves several steps. The Iris dataset is a popular dataset for classification tasks, and it consists of 150 samples of iris flowers, each with four …