5 Tribes of Machine Learning – Questions and Answers
Leading researcher Pedro Domingos answers questions on 5 tribes of Machine Learning, Master Algorithm, No Free Lunch Theorem, Unsupervised Learning, Ensemble methods, 360-degree recommender, and more.
on Nov 27, 2015 in Ensemble Methods, Machine Learning, Pedro Domingos, Recommender Systems
Detecting In-App Purchase Fraud with Machine Learning
Hacking applications allow users to make in-app purchases for free. With help from a few big games in the GROW data network we were able to build a model that classifies each purchase as real or fraud, with a very high level of accuracy.
on Nov 25, 2015 in Fraud Detection, Machine Learning, Online Games
The hardest parts of data science
The hardest part of data science is not building an accurate model or obtaining good, clean data, but defining feasible problems and coming up with reasonable ways of measuring solutions.
on Nov 24, 2015 in Data Science, Kaggle, Yanir Seroussi
What is the importance of Dark Data in Big Data world?
Dark data is a subset of big data, but it constitutes the biggest portion of the total volume of big data collected by organizations in a year. We will discuss about what opportunities this holds for an organization.
on Nov 20, 2015 in Big Data, Dark Data
The different data science roles in the industry
Data science roles and responsibilities are diverse and skills required for them vary considerably. Here, we have described the different data science roles along with the skill set, technical knowledge and mindset required to carry it.
on Nov 17, 2015 in Career, Data Analyst, Data Engineer, Data Scientist, DataCamp, Infographic, Statistician
What No One Tells You About Real-Time Machine Learning
Real-time machine learning has access to a continuous flow of transactional data, but what it really needs in order to be effective is a continuous flow of labeled transactional data, and accurate labeling introduces latency.
on Nov 9, 2015 in Dmitry Petrov, Machine Learning, Real-time
Why Deep Learning Works – Key Insights and Saddle Points
A quality discussion on the theoretical motivations for deep learning, including distributed representation, deep architecture, and the easily escapable saddle point.
on Nov 3, 2015 in Deep Learning, Distributed Representation, Matthew Mayo, Yoshua Bengio
How Data Science increased the profitability of the e-commerce industry?
Data Science helps businesses provide a richer understanding of the customers by capturing and integrating the information on customers web behaviour, their life events, what led to the purchase of a product or service, how customers interact with different channels, and more.
on Nov 3, 2015 in Data Science, DeZyre, Ecommerce, Recommendations
6 crazy things Deep Learning and Topological Data Analysis can do with your data
Want to analyze a high dimensional dataset and you are running out of options? Find out how Deep Learning combined with Topological Data Analysis can do exactly that and more.
on Nov 2, 2015 in Clustering, Data Visualization, Deep Learning, Netflix, Topological Data Analysis
5 Warning Signs that Turn Off Data Science Hiring Managers
Here are some warning signs that will prevent managers from hiring you for a Data Science position. If your resume has one or more of them, make an effort to remove the risk factors.
on Nov 2, 2015 in Data Scientist, Hiring, Kaiser Fung
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