[unable to retrieve full-text content]How to spot a beginner Data Scientist; How To Create Natural Language Semantic Search For Arbitrary Objects With Deep Learning; Statistics, Causality, and What Claims are Difficult to Swallow: Judea Pearl debates Kevin Gray; Cartoon: FIFA World Cup Football and Machine Learning
Original Post: KDnuggets™ News 18:n24, Jun 20: Data Lakes – The evolution of data processing; Text Generation with RNNs in 4 Lines of Code
[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]Extensive list of 50+ APIs in Face and Image Recognition ,Text Analysis, NLP, Sentiment Analysis, Language Translation, Machine Learning and prediction.
Original Post: 50+ Useful Machine Learning & Prediction APIs, 2018 Edition
[unable to retrieve full-text content]MeaningCloud Vertical Packs: Voice of the Customer (VoC) and Voice of the Employee (VoE), offer the fastest way to benefit from text analytics.
Original Post: The Fastest Way to Benefit from Text Analytics, Dec 20 Webinar
[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
[unable to retrieve full-text content]Although NLP and text mining are not the same thing, they are closely related, deal with the same raw data type, and have some crossover in their uses. Let’s discuss the steps in approaching these types of tasks.
Original Post: A Framework for Approaching Textual Data Science Tasks
[unable to retrieve full-text content]Also Text Clustering: Get quick insights from Unstructured Data; Using the TensorFlow API: An Introductory Tutorial Series; Deep Learning Zero to One: 5 Awe-Inspiring Demos with Code for Beginners, part 2
Original Post: KDnuggets™ News 17:n26, Jul 12: Applying Deep Learning to Real-world Problems; New Poll: Will society be better from increased automation, AI?
[unable to retrieve full-text content]We will build this in a modular way and also focus on exposing the functionalities as an API so that it can serve as a plug and play model without any disruptions to the existing systems.
Original Post: Text Clustering : Quick insights from Unstructured Data, part 2
[unable to retrieve full-text content]Grouping and clustering free text is an important advance towards making good use of it. We present an algorithm for unsupervised text clustering approach that enables business to programmatically bin this data.
Original Post: Text Clustering: Get quick insights from Unstructured Data
[unable to retrieve full-text content]We show a framework for mining relevant entities from a text resume, and how to separation parsing logic from entity specification.
Original Post: Text Mining 101: Mining Information From A Resume