[unable to retrieve full-text content]The main challenge for a data science team is to decide who will be responsible for labeling, estimate how much time it will take, and what tools are better to use.
Original Post: How to Organize Data Labeling for Machine Learning: Approaches and Tools
[unable to retrieve full-text content]This article is a comprehensive review of Data Augmentation techniques for Deep Learning, specific to images.
Original Post: Data Augmentation: How to use Deep Learning when you have Limited Data
[unable to retrieve full-text content]Machine Learning Yearning is a book by AI and Deep Learning guru Andrew Ng, focusing on how to make machine learning algorithms work and how to structure machine learning projects. Here we present 7 very useful suggestions from the book.
Original Post: 7 Useful Suggestions from Andrew Ng “Machine Learning Yearning”
[unable to retrieve full-text content]spaCy is a Python natural language processing library specifically designed with the goal of being a useful library for implementing production-ready systems. It is particularly fast and intuitive, making it a top contender for NLP tasks.
Original Post: Getting Started with spaCy for Natural Language Processing
[unable to retrieve full-text content]Learn how your predictions can only be as good as your data, how to fix imperfect data, how to structure your customer data for optimal predictive power, and more.
Original Post: Actionable Insights with Predictive Analytics for Marketers, May 9
[unable to retrieve full-text content]Most people don’t realize, but the actual “fancy” machine learning algorithm is like the last mile of the marathon. There is so much that must be done before you get there!
Original Post: The Dirty Little Secret Every Data Scientist Knows (but won’t admit)
[unable to retrieve full-text content]This post shows you how to label hundreds of thousands of images in an afternoon. You can use the same approach whether you are labeling images or labeling traditional tabular data (e.g, identifying cyber security atacks or potential part failures).
Original Post: The Value of Semi-Supervised Machine Learning
[unable to retrieve full-text content]Governance roles for data science and analytics teams are becoming more common… One of the key functions of this role is to perform analysis and validation of data sets in order to build confidence in the underlying data sets.
Original Post: Governance in Data Science
[unable to retrieve full-text content]The Technically Speaking webcast series provides real-word case studies with key insights on overcoming the challenges in data collection, preparation, and analysis – find the webcast that fits your current challenge.
Original Post: Webcasts: Finding analytic solutions to real problems
[unable to retrieve full-text content]Recently we had a look at a framework for textual data science tasks in their totality. Now we focus on putting together a generalized approach to attacking text data preprocessing, regardless of the specific textual data science task you have in mind.
Original Post: A General Approach to Preprocessing Text Data