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How to Get Hired as a Machine Learning Engineer
To become a machine learning engineer, you have to interview. You have to gain relevant skills from books, courses, conferences, and projects. Include technologies, frameworks, and projects on your CV. In an interview, expect that you will be asked technical questions, insight questions, and programming questions. When given a technical task, demonstrate your skills as if you already had the job.
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Article Series: An Introduction to Machine Learning for Software Developers
Get an introduction to some powerful but generally applicable techniques in machine learning for software developers. These include deep learning but also more traditional methods that are often all the modern business needs. After reading the articles in the series, you should have the knowledge necessary to embark on concrete machine learning experiments in a variety of areas on your own.
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Book Review: Andrew McAfee and Erik Brynjolfsson's "The Second Machine Age"
Andrew McAffee and Erik Brynjolfsson begin their book The Second Machine Age with a simple question: what innovation has had the greatest impact on human history?
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Real-World, Man-Machine Algorithms
In this article, we'll talk about the end-to-end flow of developing machine learning models: where you get training data, how you pick the ML algorithm, what you must address after your model is deployed, and so forth.
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Anomaly Detection for Time Series Data with Deep Learning
This article introduces neural networks, including brief descriptions of feed-forward neural networks and recurrent neural networks, and describes how to build a recurrent neural network that detects anomalies in time series data. To make our discussion concrete, we’ll show how to build a neural network using Deeplearning4j, a popular open-source deep-learning library for the JVM.
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Practicing Machine Learning with Optimism
Using machine learning to solve real-world problems often presents challenges that weren't initially considered during the development of the machine learning method. This article addresses a few examples of such issues and hopefully provides some suggestions (and inspiration) for how to overcome the challenges using straightforward analyses on the data you already have.
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Introduction to Machine Learning with Python
This series will explore various topics and techniques in machine learning, arguably the most talked-about area of technology and computer science over the past several years. We’ll begin, in this article, with an extended “case study” in Python: how can we build a machine learning model to detect credit card fraud?