September 25, 2020 Python

What’s New in Tensorflow 2.0?

Introduction If you are a Machine Learning Engineer, Data Scientist, or a hobbyist developing Machine Learning Models from time to time just for fun, then it is very likely that you are familiar with Tensorflow. Tensorflow is an open-source and a free framework developed by Google Brain Team written in Python, C++, and CUDA. It is used to develop, test, and deploy Machine Learning models. Initially, Tensoflow did not have full support for multiple platforms and programming languages, and it […]

September 25, 2020 Python

Deep Learning Models in Keras – Exploratory Data Analysis (EDA)

Introduction Deep learning is one of the most interesting and promising areas of artificial intelligence (AI) and machine learning currently. With great advances in technology and algorithms in recent years, deep learning has opened the door to a new era of AI applications. In many of these applications, deep learning algorithms performed equal to human experts and sometimes surpassed them. Python has become the go-to language for Machine Learning and many of the most popular and powerful deep learning libraries […]

September 25, 2020 Autoencoder

Open Source Deep Learning Frameworks and Visual Analytics

Deep Learning gets more and more traction. It basically focuses on one section of Machine Learning: Artificial Neural Networks. This article explains why Deep Learning is a game changer in analytics, when to use it, and how Visual Analytics allows business analysts to leverage the analytic models built by a (citizen) data scientist. What is Deep Learning and Artificial Neural Networks? Deep Learning is the modern buzzword for artificial neural networks, one of many concepts and algorithms in machine learning […]

September 25, 2020 Deep

Deep Learning with TensorFlow in Python

Classifying the letters with notMNIST dataset Let’s first learn about simple data curation practices, and familiarize ourselves with some of the data that are going to be used for deep learning using tensorflow. The notMNIST dataset to be used with python experiments. This dataset is designed to look like the classic MNIST dataset, while looking a little more like real data: it’s a harder task, and the data is a lot less ‘clean’ than MNIST. Preprocessing First the dataset needs to be downloaded and […]

September 25, 2020 Java

Four great machine learning eBooks

Want to learn machine learning? Looking for data science tutorials and guides to help you master your data and produce actionable, game-changing insights? Look no further than this list of machine learning eBooks from the Packt team…. 1. Python Machine Learning Python Machine Learning is today one of the most popular machine learning titles on the market. And it’s not hard to see why – by bridging the gap between theory and practice, the author Sebastian Raschka provides you with an […]

September 21, 2020 Python Leave a comment

TensorFlow: Save and Restore Models

Training a deep neural network model could take quite some time, depending on the complexity of your model, the amount of data you have, the hardware you’re running your models on, etc. On most of the occasions you’ll need to save your progress to a file, so in case of interruption (or a bug), you’ll be able to continue where you left off. Even more, after a successful training you’ll surely need to re-use the model’s learned parameters to make […]

September 21, 2020 Python Leave a comment

TensorFlow Neural Network Tutorial

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 post is concerned about its Python version, and looks at the library’s installation, basic low-level components, and building a feed-forward neural network from scratch to perform learning on a real dataset. The training […]

September 21, 2020 Python Leave a comment

Using Machine Learning to Predict the Weather: Part 3

This is the final article on using machine learning in Python to make predictions of the mean temperature based off of meteorological weather data retrieved from Weather Underground as described in part one of this series. The topic of this final article will be to build a neural network regressor using Google’s Open Source TensorFlow library. For a general introduction into TensorFlow, as well a discussion of installation methods, please see Mihajlo Pavloski’s excellent post TensorFlow Neural Network Tutorial. Topics […]

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