Why Learn Linear Algebra for Machine Learning? Linear algebra is a field of mathematics that could be called the mathematics of data. It is undeniably a pillar of the field of machine learning, and many recommend it as a prerequisite subject to study prior to getting started in machine learning. This is misleading advice, as […]

## A Gentle Introduction to Linear Algebra

What is Linear Algebra? Linear algebra is a field of mathematics that is universally agreed to be a prerequisite to a deeper understanding of machine learning. Although linear algebra is a large field with many esoteric theories and findings, the nuts and bolts tools and notations taken from the field are practical for machine learning […]

## Why Do Machine Learning Algorithms Work on Data That They Have Not Seen Before?

The superpower of machine learning is generalization. I recently got the question: “How can a machine learning model make accurate predictions on data that it has not seen before?” The answer is generalization, and this is the capability that we seek when we apply machine learning to challenging problems. In this post, you will discover […]

## How to Run Deep Learning Experiments on a Linux Server

After you write your code, you must run your deep learning experiments on large computers with lots of RAM, CPU, and GPU resources, often a Linux server in the cloud. Recently, I was asked the question: “How do you run your deep learning experiments?” This is a good nuts-and-bolts question that I love answering. In […]

## A Standard Multivariate, Multi-Step, and Multi-Site Time Series Forecasting Problem

Real-world time series forecasting is challenging for a whole host of reasons not limited to problem features such as having multiple input variables, the requirement to predict multiple time steps, and the need to perform the same type of prediction for multiple physical sites. In this post, you will discover a standardized yet complex time […]

## How to Install XGBoost for Python on macOS

XGBoost is a library for developing very fast and accurate gradient boosting models. It is a library at the center of many winning solutions in Kaggle data science competitions. In this tutorial, you will discover how to install the XGBoost library for Python on macOS. Letâ€™s get started. Tutorial Overview This tutorial is divided into […]

## How to Generate Test Datasets in Python with scikit-learn

Test datasets are small contrived datasets that let you test a machine learning algorithm or test harness. The data from test datasets have well-defined properties, such as linearly or non-linearity, that allow you to explore specific algorithm behavior. The scikit-learn Python library provides a suite of functions for generating samples from configurable test problems for […]

## How to Develop an N-gram Multichannel Convolutional Neural Network for Sentiment Analysis

A standard deep learning model for text classification and sentiment analysis uses a word embedding layer and one-dimensional convolutional neural network. The model can be expanded by using multiple parallel convolutional neural networks that read the source document using different kernel sizes. This, in effect, creates a multichannel convolutional neural network for text that reads […]

## How to Develop a Neural Machine Translation System in Keras from Scratch

Machine translation is a challenging task that traditionally involves large statistical models developed using highly sophisticated linguistic knowledge. Neural machine translation is the use of deep neural networks for the problem of machine translation. In this tutorial, you will discover how to develop a neural machine translation system for translating German phrases to English. After […]

## How to Prepare a French-to-English Dataset for Machine Translation

Machine translation is the challenging task of converting text from a source language into coherent and matching text in a target language. Neural machine translation systems such as encoder-decoder recurrent neural networks are achieving state-of-the-art results for machine translation with a single end-to-end system trained directly on source and target language. Standard datasets are required […]