Deep Learning

Population Forecasting of India using ARIMA model in Python

Applied Machine Learning and Data Science is made easy at SETScholars. SETScholars aims to guide you to become a Predictive Analytics & Data Science specialist by exploring machine learning & deep learning tools in Python, R & SQL. In this end-to-end learn by coding article, you will learn how to do an end-to-end predictive analytics project on Population Forecasting of India using ARIMA and FBProphet in Python.

TensorFlow Neural Network Tutorial in Python

Hits: 14  TensorFlow Neural Network Tutorial in Python TensorFlow is an open-source library for machine learning applications. It’s the Google Brain’s second generation system, after replacing the close-sourced DistBelief, and is used by Google for both research and production applications. TensorFlow applications can be written in a few languages: Python, Go, Java and C. This …

Learn Keras by Example – k-Fold Cross-Validating Neural Networks

Hits: 29 k-Fold Cross-Validating Neural Networks If we have smaller data it can be useful to benefit from k-fold cross-validation to maximize our ability to evaluate the neural network’s performance. This is possible in Keras because we can “wrap” any neural network such that it can use the evaluation features available in scikit-learn, including k-fold …

Learn Keras by Example – How to Visualize Performance History

Hits: 9 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 …

Learn Keras by Example – How to Visualize Neural Network Architecture

Hits: 20 Visualize Neural Network Architecture Preliminaries /* Load libraries */ from keras import models from keras import layers from IPython.display import SVG from keras.utils.vis_utils import model_to_dot from keras.utils import plot_model Using TensorFlow backend. Construct Neural Network Architecture /* Start neural network */ network = models.Sequential() /* Add fully connected layer with a ReLU activation …

Learn Keras by Example – How to Visualize Loss History

Hits: 9 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 …

Learn Keras by Example – Tuning Neural Network Hyperparameters

Hits: 13 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 …

Learn Keras by Example – Preprocessing Data For Neural Networks

Hits: 6 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 …

Learn Keras by Example – How to do Neural Network Weight Regularization

Hits: 10 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 …

Learn Keras by Example – How to do Neural Network Early Stopping

Hits: 8 Neural Network Early Stopping 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.callbacks import EarlyStopping, ModelCheckpoint /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Text Data /* Set the number of …

Learn Keras by Example – How to Build LSTM Recurrent Neural Network

Hits: 11 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 …

Machine Learning for Beginners in Python: How to Build Feedforward Neural Networks For Regression

Hits: 9 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 …

Machine Learning for Beginners in Python: How to Build Feedforward Neural Network For Multiclass Classification

Hits: 6 Feedforward Neural Network For Multiclass Classification Preliminaries /* Load libraries */ import numpy as np from keras.datasets import reuters from keras.utils.np_utils import to_categorical from keras.preprocessing.text import Tokenizer from keras import models from keras import layers /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Data /* Set the number of …

Machine Learning for Beginners in Python: How to Build Feedforward Neural Network For Binary Classification

Hits: 8 Feedforward Neural Network For Binary Classification 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 /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Data /* Set the number of features we want */ …

Learn Keras by Example – How to Build Convolutional Neural Network

Hits: 3 Convolutional Neural Network Preliminaries import numpy as np from keras.datasets import mnist from keras.models import Sequential from keras.layers import Dense, Dropout, Flatten from keras.layers.convolutional import Conv2D, MaxPooling2D from keras.utils import np_utils from keras import backend as K /* Set that the color channel value will be first */ K.set_image_data_format(‘channels_first’) /* Set seed */ …