Hits: 119 Introduction to Neural Networks with Scikit-Learn in Python What is a Neural Network? Humans have an ability to identify patterns within the accessible information with an astonishingly high degree of accuracy. Whenever you see a car or a bicycle you can immediately recognize what they are. This is because we have learned over …

Hits: 24 Visualize Performance History Preliminaries /* Load libraries */ import numpy as np from keras.datasets import imdb from keras.preprocessing.text import Tokenizer from keras import models from keras import layers import matplotlib.pyplot as plt /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Data /* Set the number of features we want …

Hits: 16 Visualize Loss History Preliminaries /* Load libraries */ import numpy as np from keras.datasets import imdb from keras.preprocessing.text import Tokenizer from keras import models from keras import layers import matplotlib.pyplot as plt /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Data /* Set the number of features we want …

Hits: 22 Tuning Neural Network Hyperparameters Preliminaries /* Load libraries */ import numpy as np from keras import models from keras import layers from keras.wrappers.scikit_learn import KerasClassifier from sklearn.model_selection import GridSearchCV from sklearn.datasets import make_classification /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Generate Target And Feature Data /* Number of features */ number_of_features …

Hits: 8 Preprocessing Data For Neural Networks Typically, a neural network’s parameters are initialized (i.e. created) as small random numbers. Neural networks often behave poorly when the feature values much larger than parameter values. Furthermore, since an observation’s feature values will are combined as they pass through individual units, it is important that all features …

Hits: 17 Neural Network Weight Regularization Preliminaries /* Load libraries */ import numpy as np from keras.datasets import imdb from keras.preprocessing.text import Tokenizer from keras import models from keras import layers from keras import regularizers /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Text Data /* Set the number of features …

Hits: 45 LSTM Recurrent Neural Network Oftentimes we have text data that we want to classify. While it is possible to use a type of convolutional network, we are going to focus on a more popular option: the recurrent neural network. The key feature of recurrent neural networks is that information loops back in the …

Hits: 66 Feed forward Neural Networks For Regression Preliminaries /* Load libraries */ import numpy as np from keras.preprocessing.text import Tokenizer from keras import models from keras import layers from sklearn.datasets import make_regression from sklearn.model_selection import train_test_split from sklearn import preprocessing /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Generate Training Data /* Generate …

Hits: 153 (How to setup MLP and CNN for MNIST dataset in Keras) In this Learn through Codes example, How to setup MLP and CNN for MNIST dataset in Keras. How_to_setup_MLP_and_CNN_for_MNIST_dataset_in_Keras Python Example for Beginners Special 95% discount 2000+ Applied Machine Learning & Data Science Recipes Portfolio Projects for Aspiring Data Scientists: Tabular …

Hits: 16 (Regression with the Keras in Python) In this Learn through Codes example, you will learn Regression with the Keras in Python. Regression_with_the_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 Data Analytics as well as …

Hits: 204 The BJ Sales dataset from UCI (University of California, Irvine) is a collection of data that is used to analyze and forecast the number of sales of a certain product over time. Each observation represents a period of time, such as a month or a year, and the feature represents the number …

Hits: 97How 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 …