-
Why Deep Learning is perfect for NLP (Natural Language Processing)
Deep learning brings multiple benefits in learning multiple levels of representation of natural language. Here we will cover the motivation of using deep learning and distributed representation for NLP, word embeddings and several methods to perform word embeddings, and applications.
-
-
Python Regular Expressions Cheat Sheet
The tough thing about learning data is remembering all the syntax. While at Dataquest we advocate getting used to consulting the Python documentation, sometimes it's nice to have a handy reference, so we've put together this cheat sheet to help you out!
-
Role of IoT in Education
In this article, I will discuss the significance of IoT and gain insights on why this technology is becoming an integral part of the daily learning and teaching methodologies.
-
Top 10 Technology Trends of 2018
By Matt Mayo on April 13, 2018 in AI, Blockchain, Chief Data Officer, Deep Learning, Ethics, IoT, NLP, Privacy, Top 10, TrendsIn this article, we will focus on the modern trends that took off well on the market by the end of 2017 and discuss the major breakthroughs expected in 2018.
-
-
Getting Started with PyTorch Part 1: Understanding How Automatic Differentiation Works
PyTorch has emerged as a major contender in the race to be the king of deep learning frameworks. What makes it really luring is it’s dynamic computation graph paradigm.
-
Comet.ml – Machine Learning Experiment Management
This article presents comet.ml – a platform that allows tracking machine learning experiments with an emphasis on collaboration and knowledge sharing.
-
Machine Learning for Text
This book covers machine learning techniques from text using both bag-of-words and sequence-centric methods. The scope of coverage is vast, and it includes traditional information retrieval methods and also recent methods from neural networks and deep learning.
-
Descriptive Statistics: The Mighty Dwarf of Data Science – Crest Factor
No other mean of data description is more comprehensive than Descriptive Statistics and with the ever increasing volumes of data and the era of low latency decision making needs, its relevance will only continue to increase.
|