Nov
2015 Dec Tutorials, Overviews, How-Tos
All (95) | Courses, Education (3) | Meetings (6) | News, Features (17) | Opinions, Interviews, Reports (37) | Publications (2) | Software (9) | Top Tweets (3) | Tutorials, Overviews, How-Tos (12) | Webcasts (6)
- Software development skills for data scientists
- Dec 29, 2015.
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.
- The Art of Data Science: The Skills You Need and How to Get Them
- Dec 28, 2015.
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.
- Tour of Real-World Machine Learning Problems
- Dec 26, 2015.
The tour lists 20 interesting real-world machine learning problems for data science enthusiasts to learn by solving.
- Everything You Need to Know about Natural Language Processing
- Dec 21, 2015.
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.
- 5 Ways Data Scientists Keep Learning After College
- Dec 17, 2015.
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.
- Top 10 Deep Learning Tips & Tricks
- Dec 14, 2015.
Deep Learning has been at the forefront of data science innovations throughout 2015. Dr. Arno Candel offers help through some valuable tips.
- Using Python and R together: 3 main approaches
- Dec 10, 2015.
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.
- Anomaly Detection in Predictive Maintenance with Time Series Analysis
- Dec 9, 2015.
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.
- 7 Essential Resources & Tips To Get Started With Data Science
- Dec 9, 2015.
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.
- Beyond One-Hot: an exploration of categorical variables
- Dec 8, 2015.
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.
- Sentiment Analysis 101
- Dec 3, 2015.
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?
- How do Neural Networks Learn?
- Dec 2, 2015.
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.
Automating Every Aspect of Your Python Project
Autograd: The Best Machine Learning Library You’re Not Using?