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Advances in Machine Learning for Software Engineering
Editor’s note: Aditya is a speaker for ODSC APAC 2021. Check out his talk, “Machine Learning for Software Engineering,” there! Today, society critically depends on software. The prevailing Covid-19 situation has accelerated the transition to a software-driven world even further. As the number of software applications... Read more
AI Experts on Different Language NLP Datasets in APAC
Natural language processing (NLP) has taken hold across every country, industry, and field of study. As language becomes the predominant form of data, researchers and data science professionals are looking at ways to harness language to obtain informative results. In the APAC region, NLP faces its... Read more
NLP in eCommerce
Computers understanding human language is a fascinating area and has piqued interest since the 1950s. 70 years later we still are continuing to solve the problem. This could be because human expressions are very varied and possibly the advancement in algorithms has yet to catch up... Read more
NLP Without a Readymade Dataset
Natural Language Processing (NLP) is a part of many day-to-day applications we use. A popular depiction of NLP is full of various algorithms, state-of-the-art neural network architectures, and so on. While it is not far from reality, it also gives an incomplete picture. A typical NLP... Read more
17 Compelling Machine Learning Ph.D. Dissertations
Working in the field of data science, I’m always seeking ways to keep current in the field and there are a number of important resources available for this purpose: new book titles, blog articles, conference sessions, Meetups, webinars/podcasts, not to mention the gems floating around in... Read more
An Introduction to Decision Tree and Ensemble Methods
In this day and age, there is a lot of buzz around machine learning (ML) and artificial intelligence (AI). And why not, after all, we all are consumers of ML directly or indirectly, irrespective of our professions. AI/ML is a fascinating field, generates a whole lot... Read more
Develop and Deploy a Machine Learning Pipeline in 45 Minutes with Ploomber
It’s standard industry practice to prototype Machine Learning pipelines in Jupyter notebooks, refactor them into Python modules and then deploy using production tools such as Airflow or Kubernetes. However, this process slows down development as it requires significant changes to the code. Ploomber enables a leaner... Read more
Allen Downey on Bayesian Methods, PyMC, and In-Demand Skills
Allen Downey, Professor of Computer Science at Olin College of Engineering, has built much of his career around Bayesian methods and the Python programming language. This in-demand skillset has been garnering increasing attention in the data science field, boosting its use in businesses and becoming more... Read more
Model Performance Optimization with TorchServe
In this blog, we are going to take a look at TorchServe, a feature-rich framework for serving machine learning models. We will go through a variety of experiments to test the performance on different operating systems, thread settings, and a number of workers to discover the... Read more
Exploring GUI of Tableau Prep Builder 
Tableau Prep Builder was introduced with version 2018.1 of Tableau Desktop, but what can we use Tableau Prep Builder (henceforth referred to in this article as Prep) for? The core purpose of the tool is data preparation. The good news is, Prep is fully compatible with Tableau Desktop, and also with Tableau Server. That means you can execute jobs in Prep to clean... Read more