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Predictive Modeling Methods and Common Data Mining Mistakes
June 22 @ 8:00 am - 3:45 pm
Predictive analytics has proven capable of enormous returns across industries – but, with so many core methods for predictive modeling, there are some tough questions that need answering:
How do you pick the right one to deliver the greatest impact for your business, as applied over your data?
What are the best practices along the way?
And how do you avoid the most treacherous pitfalls?
This one-day session surveys standard and advanced methods for predictive modeling.
Dr. Elder will describe the key inner workings of leading algorithms, demonstrate their performance with business case studies, compare their merits, and show you how to pick the method and tool best suited to each predictive analytics project. Methods covered include classical regression, decision trees, neural networks, ensemble methods, uplift modeling and more.
The key to successfully leveraging these methods is to avoid “worst practices”. It’s all too easy to go too far in one’s analysis and “torture the data until it confesses” or otherwise doom predictive models to fail where they really matter: on new situations.
Dr. Elder will share his (often humorous) stories from real-world applications, highlighting the Top 10 common, but deadly, mistakes. Come learn how to avoid these pitfalls by laughing (or gasping) at stories of barely averted disaster.
If you’d like to become a practitioner of predictive analytics – or if you already are, and would like to hone your knowledge across methods and best practices, this workshop is for you!
What you will learn:
The tremendous value of learning from data
How to create valuable predictive models for your business
Best Practices by seeing their flip side: Worst Practices
Workshop starts at 9:00am
Morning Coffee Break at 10:30am – 11:00am
Lunch provided at 12:30 – 1:15pm
Afternoon Coffee Break at 2:30pm – 3:00pm
End of the Workshop: 4:30pm
You must register to attend –
Apex and DataTorrent RTS is being actively used in use cases relating to Big Data, Cloud, IOT, CyberSecurity, Real-Time Anomaly detection, etc. This conf will help us understand how Apex can be used in these use cases.
To reduce time to market and total cost of ownership, look at operable solutions factory – that you can quickly import and launch. Examples: HDFS to HDFS & HDFS-Line-Copy (back-up, replication, disaster-recovery, distcp replacement); Kafka to HDFS (ingest, transform); S3 to HDFS (cloud to on-prem); HDFS to Kafka (data lake to event stream, big data log streaming); Database to HDFS (db offload); Database to Database (change data capture, customer 360); Kafka to Database (ingest, transform & load); Kinesis to S3 (Cloud ingest, transform, & load).
Templates include ability to parse, error check, transform, and act on before loading. Additionally, You can add/modify your custom logic on transform, alerts, and actions. Templates include real-time dashboarding for instant views and historical views.
Free DataTorrent Enterprise Edition for qualifying startups. Check it out!
Free DataTorrent Enterprise Edition for Universities. Check it out!
Brought to you by DataTorrent, creators of Apache Apex.