- The importance of effective strategic partnerships is at an all-time high. For technology companies to stay competitive and accelerate customer-focused innovation faster today, they must have a clear vision for growing their partner ecosystems. And to deliver success they need superlative collaboration both with their partners and amongst the diverse teams required within any single organization. Join us for the Partner Marketing Visionaries ™ Summit, a two-day virtual event that will explore key areas within strategic partnerships. Together, partner marketing leaders from across the globe will share insights, learnings and tactics you can use to point the way towards new levels of partner marketing success in your own practice.
- Securing endpoints is an increasingly complex undertaking as workforces grow more disparate and user devices become more diverse. It’s time to rethink your endpoint security strategies and technology to keep up with unprecedented change. Tune into the Evolution of Endpoint Security summit to hear leading experts discuss advanced and emerging endpoint security technology as well as helpful best practices for managing the chaotic endpoint environment many companies will contend with in 2023.
New Books and Courses Explore Synthetic Data, ML Strategies
MLtechniques released two new books recently. The first one, version 4.1 now, deals with synthetic data. This updated version includes a chapter on GAN (generative adversarial networks), with a comparison to more traditional methods such as copulas. Applied to real-life datasets, the author discusses the advantages and disadvantages of both methods. As always, the two methods can be blended for optimal performance.
The second book is an introduction to chaotic dynamical systems, with applications to security and strong, fast random number generators based on irrational numbers, a novelty in this field. These systems are popular in fintech, physics and social sciences. But they are under-used by machine learning professionals. The material is presented in a style and format ideal for ML practitioners, with plenty of Python code.
In addition to the books, I recently designed a synthetic data course. In the process of designing the course, I produced my first Jupyter notebook. I will share my experience with notebooks, along with Google Colab, in my upcoming Data Science Central article. I will provide my advice and opinion on this type of tool, and when they can be useful.
Contact The DSC Team if you are interested in contributing.
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