Machine Learning Archives - Software Engineering Daily

Data science is typically done by engineers writing code in Python, R, or another scripting language. Lots of engineers know these languages, and their ecosystems have great library support. But these languages have some issues around deployment, reproducibility, and other areas. The programming language Golang presents an appealing alternative for data scientists. Daniel Whitenack transitioned The post Go Data Science with Daniel Whitenack appeared first on Software Engineering Daily.

Translation is a classic problem in computer science. How do you translate a sentence from one human language into another? This seems like a problem that computers are well-suited to solve. Languages follow well-defined rules, we have lots of sample data to train our machine learning models. And yet, the problem has not been solved–largely The post Translation with Vasco Pedro appeared first on Software Engineering Daily.

Medical imaging is used to understand what is going on inside the human body and prescribe treatment. With new image processing and machine learning techniques, the traditional medical imaging techniques such as CT scans can be enriched to get a more sophisticated diagnosis. HeartFlow uses data from a standard CT scan to model a human The post Medical Machine Learning with Razik Yousfi and Leo Grady appeared first on Software Engineering Daily.

Data visualization tools are required to translate the findings of data scientists into charts, graphs, and pictures. Understanding how to utilize these tools and display data is necessary for a data scientist to communicate with people in other domains. In this episode, Srini Kadamati hosts a discussion with Jake VanderPlas about the Python ecosystem for The post Python Data Visualization with Jake VanderPlas appeared first on Software Engineering Daily.

Data engineering is the software engineering that enables data scientists to work effectively. In today’s episode, we explore the different sides of data engineering–the data science algorithms that need to be processed and the implementation of software architectures that enable those algorithms to run smoothly. The PANCAKE STACK is a 12-letter acronym that Chris Fregly The post PANCAKE STACK Data Engineering with Chris Fregly appeared first on Software Engineering Daily.

Scikit-learn is a set of machine learning tools in Python that provides easy-to-use interfaces for building predictive models. In a previous episode with Per Harald Borgen about Machine Learning For Sales, he illustrated how easy it is to get up and running and productive with scikit-learn, even if you are not a machine learning expert. The post Scikit-learn with Andreas Mueller appeared first on Software Engineering Daily.

Machine learning can be used to generate music. In the case of Feynman Liang’s research project BachBot, the machine learning model is seeded with the music of famous composer Bach. The music that BachBot creates sounds remarkably similar to Bach, although it has been generated by an algorithm, not by a human.   BachBot is The post Music Deep Learning with Feynman Liang appeared first on Software Engineering Daily.

You have probably read a news article that was written by a machine. When earnings reports come out, or a series of sports events like the Olympics occurs, there are so many small stories that need to be written that a news organization like the Associated Press would have to use all of its resources The post Automated Content with Robbie Allen appeared first on Software Engineering Daily.

Research in artificial intelligence takes place mostly at universities and large corporations, but both of these types of institutions have constraints that cause the research to proceed a certain way. In a university, basic research might be hindered by lack of funding. At a big corporation, the researcher might be encouraged to study a domain The post Artificial Intelligence with Oren Etzioni appeared first on Software Engineering Daily.

TensorFlow is Google’s open source machine learning library. Rajat Monga is the engineering director for TensorFlow. In this episode, we cover how to use TensorFlow, including an example of how to build a machine learning model to identify whether a picture contains a cat or not. TensorFlow was built with the mission of simplifying the The post TensorFlow in Practice with Rajat Monga appeared first on Software Engineering Daily.

Data Validation is the process of ensuring that data is accurate. In many software domains, an application is pulling in large quantities of data from external sources. That data will eventually be exposed to users, and it needs to be correct. Radius Intelligence is a company that aggregates data on small businesses. In order to The post Data Validation with Dan Morris appeared first on Software Engineering Daily.

Machine learning has become simplified. Similar to how Ruby on Rails made web development approachable, scikit-learn takes away much of the frustrating aspects of machine learning, and lets the developer focus on building functionality with high-level APIs.   Per Harald Borgen is a developer at Xeneta. He started programming fairly recently, but has already built The post Machine Learning for Sales with Per Harald Borgen appeared first on Software Engineering Daily.

The war against spam has been going on for decades. Email spam blockers and ad blockers help protect us from unwanted messages in our communication and browsing experience. These spam prevention tools are powered by machine learning, which catches most of the emails and ads that we don’t want to see. TrueCaller is a company The post Phone Spam with Truecaller CTO Umut Alp appeared first on Software Engineering Daily.

“Building a model to predict disease and deploying that in the wild – the bar for success is much higher there than, say, deciding what ad to show you.” Diagnosing illness today requires the trained eye of a doctor. With machine learning, we might someday be able to diagnose illness using only a data set. The post Machine Learning in Healthcare with David Kale appeared first on Software Engineering Daily.

“Nothing’s cool unless you call it ‘as a service.’ ” Monsanto is a company that is known for its chemical and biological engineering. It is less well known for its data science and software engineering teams. Tim Williamson is a data scientist at Monsanto, and on today’s show he talked about how he and a The post Data Science at Monsanto with Tim Williamson appeared first on Software Engineering Daily.

“I definitely think we can try to abstract away the first principles of intelligence and then try to go from these principles to an intelligent machine that might look nothing like the brain.” Continue reading… The post Deep Learning and Keras with François Chollet appeared first on Software Engineering Daily.

“You’ve got software engineers who are interested in machine learning, and think what they need to do is just bring in another module and then that will solve their problem. It’s particularly important for those people to understand that this is a different type of beast.” Continue reading… The post Machine Learning for Businesses with Joshua Bloom appeared first on Software Engineering Daily.

“You don’t mind if failures slow things down, but its very important that failures do not stop forward progress.” Continue reading… The post TensorFlow with Greg Corrado appeared first on Software Engineering Daily.

“I normally try to sit together or very close to a product team or engineering team. And by doing so, I get very close to the source of all kinds of challenging problems.” Continue reading… The post Data Science at Spotify with Boxun Zhang appeared first on Software Engineering Daily.

“When I was a graduate student, I was sitting in the office of my advisor in electrical engineering and he said, ‘Look out that window – you see a Volkswagon, I see a realization of a random variable.’ ” Continue reading… The post Learning Machines with Richard Golden appeared first on Software Engineering Daily.

“Changing anything changes everything.” Technical debt, referring to the compounding cost of changes to software architecture, can be especially challenging in machine learning systems. Continue reading… The post Machine Learning and Technical Debt with D. Sculley appeared first on Software Engineering Daily.

Current infrastructure makes it difficult for data scientists to share analytical models with the software engineers who need to integrate them. Yhat is an enterprise software company tackling the challenge of how data science gets done. Their products enable companies and users to easily deploy data science environments and translate analytical models into production code. Continue reading… The post Bridging Data Science and Engineering with Greg Lamp appeared first on Software Engineering Daily.

Data science competitions are an effective way to crowdsource the best solutions for challenging datasets. Kaggle is a platform for data scientists to collaborate and compete on machine learning problems with the opportunity to win money from the competitions' sponsors. Continue reading… The post Kaggle with Ben Hamner appeared first on Software Engineering Daily.

There is a need for more data scientists to make sense of the vast amounts of data we produce and store. Dataquest is an in-browser platform for learning data science that is tackling this problem. Vik Paruchuri is the founder of Dataquest. He was previously a machine learning engineer at EdX and before that a U.S. diplomat. Continue reading… The post Teaching Data Science with Vik Paruchuri appeared first on Software Engineering Daily.