Disclaimer and Publication Policy and Licensure

Aug 18 · 3 min read

Before you read our articles, contents, or view our media please check our disclaimer page (this page). It is very important to note that this article and all articles, content on our website and affiliated websites, social media, or anywhere else on the internet are for discussion / entertainment / hypothetical scenarios purpose only. They should NOT be considered professional advice. Content on this site, our affiliated sites and social media and any where else on the internet are NOT intended for commercial purpose; NOT for production purpose; NOT for professional usage.

We pay our staff writers to write and we pay for our images, medias illustration and multi-media assets, so all rights reserved. No republication / repost without permission, please.

Many discussions on this blog is highly experimental, and or informal, and or hypothetical and or theoretical. They are NOT professional advice. They are NOT education material.

Any discussion on privacy or security is strictly experimental, discussion-based or for hypothetical scenarios only. Should NOT be used for security design, implementation nor for any HIPAA related implementation. For example any differential privacy or secure AI is strictly experimental, and they are different concepts from HIPAA compliance for example. I/We are not professionals and CANNOT make any advice on GDPR nor HIPAA compliance.

We also use the following disclaimer:

Please note while we strive for best high quality accurate content, there is no guarantee that the content is accurate and always fresh. Technical tutorials can quickly become out-of-date. We will try our very best to make corrections ASAP. Any community contribution is welcome. We are a resource and informational newsletter and content blogging publisher. We do not and cannot guarantee any level of knowledge for machine learning, deep learning, or any technology on our site. Only accredited schools and training can guarantee that. We currently do not offer such courses. There is definitely no job guarantee. Machine Learning is a deep and wide field. Often PhD, research experiences and graduate level coursework are required. That being said, not every Kaggle competition winner is a PhD student. There are opportunities for novices but there is no guarantee. Though words like production, professional may be mentioned, no articles or content should be considered production nor professional advice. These contents are for informational and discussion purpose only. They should be for personal development and not used for commercial work. Thank you for your understanding. We are a tiny team of recreational writers. Please take our writing and tutorials with a grain of salt. Every effort will be made : we will always try to write accurate, succinct and informational contents.

Uniqtech writers are great technical tutorial writers, who are bootcamp graduates, free lancers, technical founders and or entrepreneurs. Uniqtech writers do not necessarily hold degrees or advanced degrees in the subject area, nor do they have education or counseling credentials, so please take all the words with a grain of salt and no words should be considered professional opinions nor should they be considered advice. That being said, our writers are effective, great communicators and know what bootcamp graduates need. We know what are the knowledge gaps and obstacles because we were in your shoes not too long ago studying these subject areas. These publications are written by bootcamp graduates for bootcamp graduates.


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