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
Technology
XLNet, ERNIE 2.0, And RoBERTa: What You Need To Know About New 2019 Transformer Models
Large pretrained language models are definitely the main trend of the latest research advances in natural language processing (NLP). While lots of AI experts agree with Anna Rogers’s statement that getting state-of-the-art results with just more data and computing power is not research news, other NLP opinion leaders also see some positive moments in the current trend. For … [Read more...] about XLNet, ERNIE 2.0, And RoBERTa: What You Need To Know About New 2019 Transformer Models
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
Getting Started with Text Preprocessing for Machine Learning & NLP
Based on some recent conversations, I realized that text preprocessing is a severely overlooked topic. A few people I spoke to mentioned inconsistent results from their NLP applications only to realize that they were not preprocessing their text or were using the wrong kind of text preprocessing for their project. With that in mind, I thought of shedding some light around … [Read more...] about Getting Started with Text Preprocessing for Machine Learning & NLP
Advanced Topics in Deep Convolutional Neural Networks
If We Want Machines to Think, We Need to Teach Them to See — Fei-Fei Li Throughout this article, I will discuss some of the more complex aspects of convolutional neural networks and how they related to specific tasks such as object detection and facial recognition. The topics that will be discussed in this tutorial are: CNN reviewReceptive Fields and Dilated … [Read more...] about Advanced Topics in Deep Convolutional Neural Networks
Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision
Introduction There is a catch to training state-of-the-art NLP models: their reliance on massive hand-labeled training sets. That’s why data labeling is usually the bottleneck in developing NLP applications and keeping them up-to-date. For example, imagine how much it would cost to pay medical specialists to label thousands of electronic health records. In general, having … [Read more...] about Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision
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
How to Deliver on Machine Learning Projects
As Machine Learning (ML) is becoming an important part of every industry, the demand for Machine Learning Engineers (MLE) has grown dramatically. MLEs combine machine learning skills with software engineering knowhow to find high-performing models for a given application and handle the implementation challenges that come up — from building out training infrastructure to … [Read more...] about How to Deliver on Machine Learning Projects