Data science and machine learning have long been interests of mine, but now that I'm working on Fuzzy.ai and trying to make AI and machine learning accessible to all developers, I need to keep on top of all the news in both fields. My preferred way to do this is through listening to podcasts. I've listened to a bunch of machine learning and data science podcasts in the last few months, so I thought I'd share my favorites: Every other week, they release a 10–15 minute episode where hosts, Kyle and Linda Polich give a short primer on topics like k-means clustering, natural language processing and decision tree learning, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings. Hosted by Katie Malone and Ben Jaffe of online education startup Udacity, this weekly podcast covers diverse topics in data science and machine learning: teaching specific concepts like Hidden Markov Models and how they apply to real-world problems and datasets.
Education has always been a hot topic among intellectuals and reformers. It has seen quite a change in the last decade or so, but not significant enough to get noticed. The new era of learning is still focused on keeping students in the classroom in the hopes that they will bring a better future to themselves and to society as a whole. The current education system has always been focused on a batch study where individual growth is never focused on. With the expansion of the internet, things have changed drastically, as now, anyone can do self-study using YouTube, Udacity, or TED.
As a research scientist at the German online retail giant Zalando, Dr. Alan Akbik is an expert in Natural Language Processing and Data Extraction. In his work for the company, which at any given moment is handling massive numbers of online transactions in multiple languages, Akbik helps unveil unique insights into the very structure of human language by observing and analyzing huge sets of multilingual text data. Here's what he had to say about the possibilities for both business and the study of language that NLP is bringing online.
As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine Learning applications are everywhere, from self-driving cars to spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this course, you'll be introduced to the Natural Processing Language and Recommendation Systems, which help you run multiple algorithms simultaneously.