Simple Machine Learning Projects

The scarcity of machine learning talent and the company's commitment to automating machine learning and completely eliminating the need for ML expertise are often on the headlines of the media.

While it may not be the development language of traditional choices for machine learning, JavaScript is proving to be able to do this—even though it currently cannot compete with the main machine learning language Python. Before we go any further, let's take a look at machine learning.

Machine learning engineers are part of the team that develops products and builds algorithms and ensures that they work reliably, quickly, and on a scale.

Open source machine learning tools also allow you to migrate learning, which means you can solve machine learning problems by applying other aspects of knowledge.

Computing is often used to analyze data, while understanding data relies on machine learning. 　　For many years, machine learning has been very remote and elusive to most developers. This is probably one of the most profitable and popular technologies now. 　　No doubt--as a developer, machine learning is a stage that can be a skill. Figure 1: Machine Learning composition machine learning is a reasonable extension of simple data retrieval and storage. 　　By developing a variety of components to make the computer more intelligent learning and behavior. Machine learning makes digging history count ...

This article is by no means comprehensive, but rather highlights the pitfalls we have seen over and over. For example, we won't talk about how to choose a good project. Some of our recommendations are generally applicable to machine learning, especially for deep learning or reinforcement learning research projects.

Today, I will share all the questions I encountered during the interview and share how to answer them. Some of these questions are relatively normal and have a certain theoretical background, but some are very innovative.

Introduction: It is well known that R is unparalleled in solving statistical problems. But R is slow at data speeds up to 2G, creating a solution that runs distributed algorithms in conjunction with Hadoop, but is there a team that uses solutions like python + Hadoop? R Such origins in the statistical computer package and Hadoop combination will not be a problem? The answer from the king of Frank: Because they do not understand the characteristics of R and Hadoop application scenarios, just ...

It was probably 2008, when China set off a wave of shanzhai phones, in this crazy and barbaric era, the entire product from the project to trial production, and then to the amount of output, the time required often less than two weeks, assembly line is also short to die, also about 10 meters away, as for, the test is even more rough, Some mobile phones even directly download software shipments ... However, because of bypassing detailed functional testing and routine testing projects, the Shanzhai machine occupies an overwhelming advantage in cost, a color mobile phone only sell 200 yuan, really let domestic consumers heartbeat. In just two years time, not only the birth ...

Editor's note: The concept of deep learning stems from the study of artificial neural networks. As a kind of artificial intelligence, "depth learning" is a training system that can handle massive amounts of information from audio, images and other input signals, and if new information is presented to the system, it will respond in the form of inferences. Technology companies such as Google and Facebook have made technological advances and mergers and acquisitions in this area, and "deep learning" start-ups are springing up. Richard Socher, a graduate student at Stanford University, created the meta after graduation ...