Vector Space - Notion Knowledge Base for AI Engineers

Are you an AI engineer or want to become one? You are at the right place; our product, Vector Space - Notion Template for AI Engineers, is a curated and organized resources hub built on top of Notion that you could gain access to for a lifetime through our channel - Gumroad.

What is Vector Space - Knowledge Base for AI Engineers?

Vector Space is an all-in-one knowledge base built on Notion to help new and experienced AI engineers learn more about the elements of building generative AI applications.

Can this product help me to become an AI engineer?

Answer: Yes, of course.

This template is a comprehensive starter kit to kickstart your learning journey to becoming an AI engineer! The product includes a customized GPT called Victor on ChatGPT to help you accelerate the learning curve.

Will I be an AI engineer by just using this guide?

Answer: No

This product serves as a map and tutor guide for tapping into this new and fast-paced field of technologies and development community. I highly recommend using this guide as a starting point to find out more!

Life-time Update

The field of generative AI is highly dynamic and fast-paced. Therefore, we provide lifetime updates to all our clients who purchase the product at any time. Please subscribe to our newsletters at https://mindifyai.substack.com/.

Customers Support

Feel free to contact customer support at Mindify AI via support@mindifyai.dev.

Checkout Reminder

We recommend using VISA/Mastercard to purchase the product instead of PayPal due to the risk of the transaction being blocked by PayPal. Ref: https://help.gumroad.com/article/266-why-are-my-customers-purchases-failing#PayPal-Is-Blocking-their-Purchase-25EcI

About the creator, Mark (Founder of Mindify AI)

Mark is a computer science student in the international program at the University of London and a tech entrepreneur who is building an AI solution company. He works as a research scientist with institutions in Taiwan, focusing on machine intelligence with quantum computing and innovative algorithms. Mark has published two papers with an m-index of 2 and over 1600 article accesses in six months. His work centers on alignment research for LLM, engineering practical quantum algorithms, and delivering courses on generative AI. Mark's principle is iterative and continuous growth to build, learn, and iterate his products, solutions, and scientific works.