Handwritten Digit Recognition using Convolutional Neural Networks in Python with Keras

Last Updated on August 27, 2020 A popular demonstration of the capability of deep learning techniques is object recognition in image data. The “hello world” of object recognition for machine learning and deep learning is the MNIST dataset for handwritten digit recognition. In this post you will discover how to develop a deep learning model to achieve near state of the art performance on the MNIST handwritten digit recognition task in Python using the Keras deep learning library. After completing […]

September 29, 2020 Machine Learning

Standard Machine Learning Datasets To Practice in Weka

Last Updated on December 11, 2019 It is a good idea to have small well understood datasets when getting started in machine learning and learning a new tool. The Weka machine learning workbench provides a directory of small well understood datasets in the installed directory. In this post you will discover some of these small well understood datasets distributed with Weka, their details and where to learn more about them. We will focus on a handful of datasets of differing […]

September 29, 2020 Machine Learning

Image Augmentation for Deep Learning With Keras

Last Updated on September 13, 2019 Data preparation is required when working with neural network and deep learning models. Increasingly data augmentation is also required on more complex object recognition tasks. In this post you will discover how to use data preparation and data augmentation with your image datasets when developing and evaluating deep learning models in Python with Keras. After reading this post, you will know: About the image augmentation API provide by Keras and how to use it […]

September 29, 2020 Machine Learning

How to Better Understand Your Machine Learning Data in Weka

Last Updated on August 22, 2019 It is important to take your time to learn about your data when starting on a new machine learning problem. There are key things that you can look at to very quickly learn more about your dataset, such as descriptive statistics and data visualizations. In this post you will discover how you can learn more about your data in the Weka machine learning workbench my reviewing descriptive statistics and visualizations of your data. After […]

September 29, 2020 Machine Learning

Object Classification with CNNs using the Keras Deep Learning Library

Last Updated on August 27, 2020 Keras is a Python library for deep learning that wraps the powerful numerical libraries Theano and TensorFlow. A difficult problem where traditional neural networks fall down is called object recognition. It is where a model is able to identify the objects in images. In this post, you will discover how to develop and evaluate deep learning models for object recognition in Keras. After completing this tutorial you will know: About the CIFAR-10 object classification […]

September 29, 2020 Machine Learning

How to Predict Sentiment From Movie Reviews Using Deep Learning (Text Classification)

Last Updated on August 27, 2020 Sentiment analysis is a natural language processing problem where text is understood and the underlying intent is predicted. In this post, you will discover how you can predict the sentiment of movie reviews as either positive or negative in Python using the Keras deep learning library. After reading this post you will know: About the IMDB sentiment analysis problem for natural language processing and how to load it in Keras. How to use word […]

September 29, 2020 Machine Learning

How to Normalize and Standardize Your Machine Learning Data in Weka

Last Updated on December 11, 2019 Machine learning algorithms make assumptions about the dataset you are modeling. Often, raw data is comprised of attributes with varying scales. For example, one attribute may be in kilograms and another may be a count. Although not required, you can often get a boost in performance by carefully choosing methods to rescale your data. In this post you will discover how you can rescale your data so that all of the data has the […]

September 29, 2020 Machine Learning

Applied Deep Learning in Python Mini-Course

Last Updated on December 11, 2019 Deep learning is a fascinating field of study and the techniques are achieving world class results in a range of challenging machine learning problems. It can be hard to get started in deep learning. Which library should you use and which techniques should you focus on? In this post you will discover a 14-part crash course into deep learning in Python with the easy to use and powerful Keras library. This mini-course is intended for […]

September 29, 2020 Machine Learning

Crash Course in Recurrent Neural Networks for Deep Learning

Last Updated on August 14, 2019 There is another type of neural network that is dominating difficult machine learning problems that involve sequences of inputs called recurrent neural networks. Recurrent neural networks have connections that have loops, adding feedback and memory to the networks over time. This memory allows this type of network to learn and generalize across sequences of inputs rather than individual patterns. A powerful type of Recurrent Neural Network called the Long Short-Term Memory Network has been […]

September 29, 2020 Machine Learning

How to Transform Your Machine Learning Data in Weka

Last Updated on December 13, 2019 Often your raw data for machine learning is not in an ideal form for modeling. You need to prepare or reshape it to meet the expectations of different machine learning algorithms. In this post you will discover two techniques that you can use to transform your machine learning data ready for modeling. After reading this post you will know: How to convert a real valued attribute into a discrete distribution called discretization. How to […]

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