I spoke at a conference recently and one of the talks really resonated with me. It revolved around hosting, securing, and productionizing machine learning models. The speaker asked the audience, “Who in this room has developed a machine learning or artificial intelligence model for their business?” Being a technology conference, 80–90% of the hands shot up. “Now,” he … [Read more...] about 4 Common Pitfalls In Putting A Machine Learning Model In Production
Technology
How To Crowdsource Labeled Datasets Quickly With Open-Source Tools Like Snorkel
Getting sufficient amounts of labeled training data is a major bottleneck for many machine learning (ML) projects. You can create fancy models but they will be of little value if domain experts need to spend years labeling the relevant dataset. That is particularly relevant in areas where high expertise is required from data labelers, like, for example, in medical applications … [Read more...] about How To Crowdsource Labeled Datasets Quickly With Open-Source Tools Like Snorkel
How Airbnb Solves Enterprise-Scale Data Challenges For Machine Learning
Traditional data warehouses are built for Business Intelligence analytics, CEO Dashboards, and other types of business reporting prepared for “human consumption.” That often implies that data in these warehouses is not ready for “machine consumption,” including machine learning (ML) models. For example, it is mostly sufficient for humans to know the date of a particular event, … [Read more...] about How Airbnb Solves Enterprise-Scale Data Challenges For Machine Learning
Solving Data Challenges In Machine Learning With Automated Tools
Data is the lifeblood of machine learning (ML) projects. At the same time, the data preparation process is one of the main challenges that plague most projects. According to a recent study, data preparation tasks take more than 80% of the time spent on ML projects. Data scientists spend most of their time on data cleaning (25%), labeling (25%), augmentation (15%), aggregation … [Read more...] about Solving Data Challenges In Machine Learning With Automated Tools
Overview of the Different Approaches to Putting Machine Learning Models in Production
There are different approaches to putting models into production with benefits that can vary dependent on the specific use case. Take, for example, the use case of churn prediction. It is beneficial to have a static value that can be easily looked up when someone calls customer service, but there is some extra value that could be gained if, for specific events, the model could … [Read more...] about Overview of the Different Approaches to Putting Machine Learning Models in Production
Everything a Data Scientist Should Know About Data Management*
(*But Was Afraid to Ask) To be a real “full-stack” data scientist, or what many bloggers and employers call a “unicorn,” you’ve to master every step of the data science process — all the way from storing your data, to putting your finished product (typically a predictive model) in production. But the bulk of data science training focuses on machine/deep learning techniques; … [Read more...] about Everything a Data Scientist Should Know About Data Management*
Neural Style Transfer and Visualization of Convolutional Networks
Likewise, we admire the story of musicians, artists, writers and every creative human because of their personal struggles, how they overcome life’s challenges and find inspiration from everything they’ve been through. That’s the true nature of human art. That’s something that can’t be automated, even if we achieve the always-elusive general artificial intelligence. — Ray … [Read more...] about Neural Style Transfer and Visualization of Convolutional Networks
An Introduction to Super Resolution Using Deep Learning
Introduction Super Resolution is the process of recovering a High Resolution (HR) image from a given Low Resolution (LR) image. An image may have a “lower resolution” due to a smaller spatial resolution (i.e. size) or due to a result of degradation (such as blurring). We can relate the HR and LR images through the following equation: [latex]LR = … [Read more...] about An Introduction to Super Resolution Using Deep Learning
Top NLP Research Trends From ACL 2019
This year, I had the chance to attend the ACL 2019 conference in Florence. It was my first NLP academic conference, and I was eager to attend as many sessions as possible. In contrast to most of the attendees, I was not interested in any particular research area. Instead, I wanted to pick up on the general NLP trends - so I was happy to hear about the latest advances in … [Read more...] about Top NLP Research Trends From ACL 2019
Top NLP Research Papers With Business Applications From ACL 2019
This year’s annual meeting of the Association for Computational Linguistics (ACL 2019) was bigger than ever. Although the conference received 75% more submissions than last year, the quality of the research papers remained high, and so the acceptance rates are almost the same. It is becoming more and more challenging to keep track of the latest research advances in your area … [Read more...] about Top NLP Research Papers With Business Applications From ACL 2019