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The Coolest Natural Language Processing Applications
Natural Language Processing (NLP) is one of the most interesting areas of Data Science. From analysis of the political arena, to organizing meetings, and forming the bedrock of the dream of strong A.I, training computers to truly understand the nuances of human language is part of the yet unreached... Read more
Over time, Python and R have established themselves as the leading languages for Data Science. The rise of both has not been frictionless, though, as the two communities have ‘clashed’ over philosophical differences as each side recruits Data Science newcomers. R users will recommend that R is the better... Read more
Data science is an interdisciplinary endeavor, and it serves the purpose of extracting insight from varying sources of information. Various communities come together at Data Science Conferences to share their knowledge and promote innovation. It is not surprising, then, that the tools showcased by data scientists at ODSC East... Read more
Amazon Machine Learning: Nice and Easy or Overly Simple?
Can the new Amazon Machine Learning help companies reap the benefits of predictive analytics? Machine Learning as a Service (MLaaS) promises to put data science within the reach of companies. In that context, Amazon Machine Learning is a predictive analytics service with binary/multiclass classification and linear regression features. The service... Read more
Jupyter, Zeppelin, Beaker: The Rise of the Notebooks
Standard software development practices for web, Saas, and industrial environments tend to focus on maintainability, code quality, robustness, and performance. Scientific programing in data science is more concerned with exploration, experimentation, making demos, collaborating, and sharing results. It is this very need for experiments, explorations, and collaborations that is... Read more
Standard software development practices for web, Saas, and industrial environments tend to focus on maintainability, code quality, robustness, and performance. Scientific programing in data science is more concerned with exploration, experimentation, making demos, collaborating, and sharing results. It is this very need for experiments, explorations, and collaborations that is... Read more
Intro to Text mining using R
Abstract: Attendees will learn the foundations of text mining approaches in addition to learn basic text mining scripting functions used in R. The audience will learn what text mining is, then perform primary text mining such as keyword scanning, dendogram and word cloud creation. Later participants will be able... Read more
Riding on Large Data with Scikit-learn
What’s a Large Data Set? A data set is said to be large when it exceeds 20% of the available RAM for a single machine. Which for your standard MacBook Pro with 8Gb of RAM, corresponds to a meager 2Gb dataset — size that is becoming more and more... Read more
Saul Diez-Guerra at ODSC Boston 2015
What We Learned While Teaching Python and Data Science Pedagogy and lessons learned from teaching an online introductory Python and Data Science courses. This is how we approached the matter, what we learned and where we want to go next. Presenter Bio: Saul Diez-Guerra works as Engineering Lead at... Read more
Scikit-Learn for Easy Machine Learning: the Vision, the Tool, and the Project Scikit-learn for easy machine learning: the vision, the tool, and the project from Gael Varoquaux Scikit-learn is a popular machine learning tool. What can it do for you?Why you you want to use it? What can you... Read more