Software development skills for data scientists
Data science is not only about building the models and sharing insights, many times they have to collaborate in deploying models and sharing them with software developers, learn which things to keep in mind while doing so.
on Dec 29, 2015 in Data Science Skills, Software, Trey Causey
The Art of Data Science: The Skills You Need and How to Get Them
Learn, how to turn the deluge of data into the gold by algorithms, feature engineering, reasoning out business value and ultimately building a data driven organization.
on Dec 28, 2015 in Algorithms, Data Science Skills, Feature Engineering, MapR
Tour of Real-World Machine Learning Problems
The tour lists 20 interesting real-world machine learning problems for data science enthusiasts to learn by solving.
on Dec 26, 2015 in Datasets, Kaggle, Learning from Data, Machine Learning, Research, UCI
Everything You Need to Know about Natural Language Processing
Natural language processing (NLP) helps computers understand human speech and language. We define the key NLP concepts and explain how it fits in the bigger picture of Artificial Intelligence.
on Dec 21, 2015 in API, Buzzlogix, NLP, Text Analytics, Text Mining
5 Ways Data Scientists Keep Learning After College
Taken from the answers experts gave, here is a compiled list of 5 essential actions and attitudes that keep data scientists learning after their degrees.
on Dec 17, 2015 in Advice, Data Scientist, Experts, Interview, Kaggle, MOOC, Tools
Top 10 Deep Learning Tips & Tricks
Deep Learning has been at the forefront of data science innovations throughout 2015. Dr. Arno Candel offers help through some valuable tips.
on Dec 14, 2015 in Arno Candel, Deep Learning, H2O, Machine Learning, Tips, Top 10
Using Python and R together: 3 main approaches
Well if Data Science and Data Scientists can not decide on what data to choose to help them decide which language to use, here is an article to use BOTH.
on Dec 10, 2015 in Ajay Ohri, Jupyter, Python, Python vs R, R
Anomaly Detection in Predictive Maintenance with Time Series Analysis
How can we predict something we have never seen, an event that is not in the historical data? This requires a shift in the analytics perspective! Understand how to standardization the time and perform time series analysis on sensory data.
on Dec 9, 2015 in Anomaly Detection, Knime, Rosaria Silipo, Time Series
7 Essential Resources & Tips To Get Started With Data Science
This instructional post takes you through connecting the various pieces when studying the data science pipeline. From analysis, to datasets, to MOOCs, to visualizing data, this informative post has some fresh insight.
on Dec 9, 2015 in Data Science, Data Science Education, Data Visualization
Beyond One-Hot: an exploration of categorical variables
Coding categorical variables into numbers, by assign an integer to each category ordinal coding of the machine learning algorithms. Here, we explore different ways of converting a categorical variable and their effects on the dimensionality of data.
on Dec 8, 2015 in Data Exploration, Machine Learning, Python, Will McGinnis
Sentiment Analysis 101
Sentiment analysis can be incredibly useful, and can help companies better answer pertinent questions and gain valuable business insights. Sentiment analysis technologies will continue to improve as they become more widely adopted. But what can sentiment analysis do for you?
on Dec 3, 2015 in Buzzlogix, NLP, Sentiment Analysis
How do Neural Networks Learn?
Neural networks are generating a lot of excitement, while simultaneously posing challenges to people trying to understand how they work. Visualize how neural nets work from the experience of implementing a real world project.
on Dec 2, 2015 in Backpropagation, Graph Visualization, Neural Networks
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