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
Applied AI
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
20 Criteria You Should Use To Choose A Data Catalog
The Roles of a Data Catalog The difficulties of data management have intensified at a steady pace over the past several years. The management complexities of big data, cloud hosting, self-service analytics, and tightening regulations can’t be ignored. Effective data management has become a top priority for most organizations, but getting there is challenging. Data catalogs … [Read more...] about 20 Criteria You Should Use To Choose A Data Catalog
How to Organize Data Labeling for Machine Learning: Approaches and Tools
If there was a data science hall of fame, it would have a section dedicated to labeling. The labelers’ monument could be Atlas holding that large rock symbolizing their arduous, detail-laden responsibilities. ImageNet — an image database — would deserve its own style. For nine years, its contributors manually annotated more than 14 million images. Just thinking about it makes … [Read more...] about How to Organize Data Labeling for Machine Learning: Approaches and Tools
Machine Learning Project Structure: Stages, Roles, and Tools
Various businesses use machine learning to manage and improve operations. While ML projects vary in scale and complexity requiring different data science teams, their general structure is the same. For example, a small data science team would have to collect, preprocess, and transform data, as well as train, validate, and (possibly) deploy a model to do a single … [Read more...] about Machine Learning Project Structure: Stages, Roles, and Tools
Major Challenges for Machine Learning Projects
Although scientists, engineers, and business mavens agree we might have finally entered the golden age of artificial intelligence when planning a machine learning project you have to be ready to face much more obstacles than you think. Deep learning algorithms like AlphaGo are breaking one frontier after another, proving that machines can already be able to play complex … [Read more...] about Major Challenges for Machine Learning Projects
What Is This “AI For Social Good”?
The “AI for Social Good” umbrella “AI for social good”. We increasingly see related initiatives by organisations like Google and Microsoft, conferences, reports and workshops in major “AI” conferences like Neurips, ICRL, and ICML. However, AI for good has become an arbitrary term. Not only AI is a conflated term (for which we can write books about) but … [Read more...] about What Is This “AI For Social Good”?
How to Create a Fake Video of a Real Person
Recent advances in artificial intelligence have made creating convincing fake videos, or deepfakes, of real people possible. While the ethical implications and the creative capabilities of this amazing technology are only beginning to be explored, there are growing concerns that this technology could be used maliciously to ruin reputations and cause extensive damages. Can … [Read more...] about How to Create a Fake Video of a Real Person