Join Barton Poulson for an in-depth discussion in this video Next steps, part of Data Science Foundations: Data Mining.
- [Instructor] Thanks for joining me,…and learning more about data mining,…and how you can use these tools and these practices…to get more information and better understand now…the data that's all around you.…If you wanna learn more about data mining…and data science in general,…I've got a few general recommendations…for things you can do.…First of course is here at Lynda.com,…we have an entire collection of big data tutorials…that apply beautifully to data mining…and data science as well.…At this exact moment,…there are 26 other courses on…Hadoop, and Google Data Studio, et cetera.…
And I strongly encourage you to take a look of what's there…and get some other excellent resources and perspectives…on working with data.…For general resources,…one of the best is going to be KDNuggets.…KD stands for Knowledge Discovery.…This is an overall website for links to information…about what's going on in data mining.…It's also one of the best sources for the tools…that people are using in the field.…Once you're ready to to start working with some data,…
Barton Poulson covers data sources and types, the languages and software used in data mining (including R and Python), and specific task-based lessons that help you practice the most common data-mining techniques: text mining, data clustering, association analysis, and more. This course is an absolute necessity for those interested in joining the data science workforce, and for those who need to obtain more experience in data mining.
- Prerequisites for data mining
- Data mining using R, Python, Orange, and RapidMiner
- Data reduction
- Data clustering
- Anomaly detection
- Association analysis
- Regression analysis
- Sequence mining
- Text mining
Skill Level Beginner
Transitioning from Data Warehousing to Big Datawith Alan Simon1h 50m Intermediate
Big Data Foundations: Program Managementwith Alan Simon1h 11m Intermediate
2. Data Reduction
5. Anomaly Detection
6. Association Analysis
7. Regression Analysis
8. Sequential Patterns
9. Text Mining
Next steps1m 18s
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