Tag Archives: deep learning

Binary Classification with Sonar Dataset: Baseline Keras Model in Python

(Binary Classification with Sonar Dataset: Baseline Keras Model in Python) In this Learn through Codes example, you will learn Binary Classification with Sonar Dataset: Baseline Keras Model in Python.  Binary_Classification_with_Sonar_Dataset_Baseline_Keras_Model_in_Python   Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text …

How to do multi-class classification with Keras in Python

(How to do multi-class classification with Keras in Python) In this Learn through Codes example, you will learn how to do multi-class classification with Keras in Python.  How_to_multi-class_classification_with_Keras_in_Python   Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text & Image …

Keras Deep Learning with Grid Search using sklearn

(Keras Deep Learning with Grid Search using sklearn) In this Learn through Codes example, you will learn Keras Deep Learning with Grid Search using sklearn.  Keras_Deep_Learning_with_Grid_Search_using_sklearn Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text & Image Data Analytics as …

Keras Deep Learning with 10-fold cross validation using sklearn

(Keras Deep Learning with 10-fold cross validation using sklearn) In this Learn through Codes example, you will learn Keras Deep Learning with 10-fold cross validation using sklearn.  Keras_Deep_Learning_with_10-fold_cross_validation_using_sklearn Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular Text & Image Data …

How to install, load and describe Penn Machine Learning Benchmarks – Yeast Datasets

How to install, load and describe Penn Machine Learning Benchmarks – Yeast Datasets   The Penn Machine Learning Benchmarks (PMLB) is a collection of datasets for evaluating machine learning algorithms. One of the datasets included in PMLB is the Yeast dataset, which consists of 14 different datasets related to the yeast Saccharomyces cerevisiae. In this …

How to use deep learning through sklearn in classifying adult dataset

How to use deep learning through sklearn in classifying adult dataset   Deep learning is a powerful technique for classifying complex datasets such as the adult dataset. In this essay, we will be discussing how to use deep learning through sklearn, a popular machine learning library in Python, to classify the adult dataset. The first …

How to use Keras and Tensorflow in classifing adult income data in Python

How to use Keras and Tensorflow in classifing adult income data in Python     Classifying the adult income dataset using Keras and Tensorflow is a popular machine learning task that involves training a model to predict whether an individual’s income is above or below a certain threshold. In this essay, we will be discussing …

How to predict a time series using GRU in Keras

How to predict a time series using GRU in Keras     A Gated Recurrent Unit (GRU) is a type of Recurrent Neural Network (RNN) that can be used to predict a time series. RNNs are particularly useful for time series prediction tasks because they are able to process sequential data and maintain a memory …

How to predict a time series using LSTM in Keras

How to predict a time series using LSTM in Keras     A Long Short-Term Memory (LSTM) network is a type of Recurrent Neural Network (RNN) that can be used to predict a time series. RNNs are particularly useful for time series prediction tasks because they are able to process sequential data and maintain a …

How to predict and visualise a time series using GradientBoost in Python

How to predict and visualise a time series using GradientBoost in Python     Gradient Boosting is an ensemble technique that can be used to predict and visualize time series data. It is a powerful machine learning algorithm that combines multiple weak models to create a stronger model that can make predictions with high accuracy. …