- Amazon Top 20 Books in Neural Networks - Nov 30, 2015.
These are the most popular neural networks books on Amazon. Perhaps there is something of interest to you here.
Amazon, Book, Deep Learning, Matthew Mayo, Neural Networks
- 5 Tribes of Machine Learning – Questions and Answers - Nov 27, 2015.
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.
Ensemble Methods, Machine Learning, Pedro Domingos, Recommender Systems
- Detecting In-App Purchase Fraud with Machine Learning - Nov 25, 2015.
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.
Fraud Detection, Machine Learning, Online Games
- Career path explained: Big Data Hadoop DEVELOPER to ARCHITECT - Nov 24, 2015.
The path to becoming a Big Data and Hadoop Architect is fraught with major challenges and responsibilities, but here is a handy infographic to help you chart out your path.
Big Data, Big Data Architect, Developer, Hadoop, Simplilearn
- The hardest parts of data science - Nov 24, 2015.
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.
Data Science, Kaggle, Yanir Seroussi
- Top KDnuggets tweets, Nov 16-22: Dilbert discovers the perfect chart; TensorFlow Disappoints – Google Deep Learning falls shallow - Nov 23, 2015.
A standard #graph for any occasion! #Dilbert discovers the perfect chart; TensorFlow Disappoints - Google #DeepLearning falls shallow; All the #BigData tools and how to use them; KDnuggets #DataScience #Cartoon Caption Contest.
Cartoon, Deep Learning, Dilbert, James Bond, TensorFlow, Tesla
- What is the importance of Dark Data in Big Data world? - Nov 20, 2015.
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.
Big Data, Dark Data
- Deep Learning for Visual Question Answering - Nov 19, 2015.
Here we discuss about the Visual Question Answering problem, and I’ll also present neural network based approaches for same.
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Deep Learning, Question answering, Turing Test
- 7 Steps to Mastering Machine Learning With Python - Nov 19, 2015.
There are many Python machine learning resources freely available online. Where to begin? How to proceed? Go from zero to Python machine learning hero in 7 steps!
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7 Steps, Anaconda, Caffe, Deep Learning, Machine Learning, Matthew Mayo, Python, scikit-learn, Theano
- The different data science roles in the industry - Nov 17, 2015.
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.
Career, Data Analyst, Data Engineer, Data Scientist, DataCamp, Infographic, Statistician
- Getting started with Python and Apache Flink - Nov 13, 2015.
Apache Flink built on top of the distributed streaming dataflow architecture, which helps to crunch massive velocity and volume data sets. With version 1.0 it provided python API, learn how to write a simple Flink application in python.
Flink, Python, Realtime Analytics, Streaming Analytics, Will McGinnis
- A Statistical View of Deep Learning - Nov 13, 2015.
A statistical overview of deep learning, with a focus on testing wide-held beliefs, highlighting statistical connections, and the unseen implications of deep learning. The post links to 6 articles covering a number of related topics.
Deep Learning, Recurrent Neural Networks, Statistical Learning
- Understanding Convolutional Neural Networks for NLP - Nov 11, 2015.
Dive into the world of Convolution Neural Networks (CNN), learn how they work, how to apply them for NLP, and how to tune CNN hyperparameters for best performance.
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Convolutional Neural Networks, Deep Learning, Neural Networks, NLP
- Fast Big Data: Apache Flink vs Apache Spark for Streaming Data - Nov 10, 2015.
Real-time stream processing has been gaining momentum in recent past, and major tools which are enabling it are Apache Spark and Apache Flink. Learn with the help of a case study about Data processing, Data Flow, Data management using these tools.
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Apache Spark, Big Data, Flink, Streaming Analytics
- Data Science of IoT: Sensor fusion and Kalman filters, Part 2 - Nov 9, 2015.
The second part of this tutorial examines use of Kalman filters to determine context for IoT systems, which helps to combine uncertain measurements in a multi-sensor system to accurately and dynamically understand the physical world.
FutureText, IoT, Kalman Filters, Sensors
- What No One Tells You About Real-Time Machine Learning - Nov 9, 2015.
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.
Dmitry Petrov, Machine Learning, Real-time
- Topological Data Analysis – Open Source Implementations - Nov 6, 2015.
Topological Data Analysis (TDA) is making waves in the analytics community lately, but are there open source options available?
C++, Java, Matthew Mayo, Open Source, Python, R, Topological Data Analysis
- 5 Best Machine Learning APIs for Data Science - Nov 5, 2015.
Machine Learning APIs make it easy for developers to develop predictive applications. Here we review 5 important Machine Learning APIs: IBM Watson, Microsoft Azure Machine Learning, Google Prediction API, Amazon Machine Learning API, and BigML.
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Amazon, API, Azure ML, BigML, DeZyre, Google, IBM Watson, Machine Learning
- Cartoon: It all started with the iPhone answering my email - Nov 5, 2015.
New KDnuggets cartoon reacts to recent news that Gmail will use Machine Learning to offer answers to your emails. Here is where it can lead ...
Cartoon, Gmail, iPhone
- Data-Planet Statistical Datasets - Nov 4, 2015.
Data-Planet Statistical Datasets provides easy access to an extensive repository of standardized and structured statistical data, with more than 25 billion data points from more than 70 source organizations.
Data Platform, Statistics, Time Series, Time series data
- Why Deep Learning Works – Key Insights and Saddle Points - Nov 3, 2015.
A quality discussion on the theoretical motivations for deep learning, including distributed representation, deep architecture, and the easily escapable saddle point.
Deep Learning, Distributed Representation, Matthew Mayo, Yoshua Bengio
- Overview of Python Visualization Tools - Nov 3, 2015.
An overview and comparison of the leading data visualization packages and tools for Python, including Pandas, Seaborn, ggplot, Bokeh, pygal, and Plotly.
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Data Visualization, ggplot2, Pandas, Plotly, Python
- How Data Science increased the profitability of the e-commerce industry? - Nov 3, 2015.
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.
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Data Science, DeZyre, Ecommerce, Recommendations
- 6 crazy things Deep Learning and Topological Data Analysis can do with your data - Nov 2, 2015.
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.
Clustering, Data Visualization, Deep Learning, Netflix, Topological Data Analysis
- 5 Warning Signs that Turn Off Data Science Hiring Managers - Nov 2, 2015.
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.
Data Scientist, Hiring, Kaiser Fung