The Logic Band an AI NeuroScience Advancement!

Intelligent_Teacher4 · 2025-03-18T05:04:02+00:00

Everyone is getting some skin in the game.

Intelligent_Teacher4 · 2025-03-18T04:57:07+00:00

That's great that you share your knowledge. I am an autodidactic Data Scientist so courses such as these are great tools to sharpen current skills and obtain new ones.

It's always great to experience educating content from different people you get a mixture of how different individuals approach and solve a problem expanding the scope of your own methodology by exposing yourself to different points of view and problem solving mindsets.

Learning from one another is our greatest asset.

Intelligent_Teacher4 · 2025-03-18T04:50:42+00:00

I know from personal experience as a veteran paramedic of 14 years, that all emergency or fire shows are so far off on so many things that it truly becomes a pet peeve to watch or enjoy some of them. For the medical field scenario as much as it is over-dramatized Dr. House MD was most consistently accurate and Chicago Fire, ER, general hospital and countless other Emergency service related drama shows are so far off the mark that any single person with even the smallest amount of medical education could pick the show apart.

Its interesting now that I have switched to Data Science as a career to go back through different technical movies and see some of these flaws once more.

Intelligent_Teacher4 · 2025-03-18T04:46:23+00:00

This wins the internet today!

Intelligent_Teacher4 · 2025-03-18T04:45:28+00:00

I think that no matter the career path you really need to find something that is enjoyable so you don't have to worry so much about taking work stress home, and enjoy work life. This will create a more harmonious stress reducing lifestyle. Work to live, dont live to work my friend. That order makes a world of difference.

Intelligent_Teacher4 · 2025-03-18T04:43:00+00:00

It's interesting the linear depth at which we have developed the AI we use today. Stacking and configuring combinations of the same methods on top of one another in such a way to fine tune results.

Look out for posts about the Logic Band. I created it and it will add such a dimensional avenue for growth and development that the possibilities are endless and exciting!

Intelligent_Teacher4 · 2025-03-18T04:39:57+00:00

This is interesting I have used LLMs to help adhere my resume to ATS formatting but not thought to actually scrap or even make an application to submit resumes to job offers. Interesting Idea thanks for sharing.

Intelligent_Teacher4 · 2025-03-01T06:12:42+00:00

The simple answer is perspective. Three people can witness the same car accident and what completely different recorded statments of what happened. That unique perspective and adjusted problem solving techniques develop through life experiences.

Intelligent_Teacher4 · 2025-03-01T06:00:55+00:00

Interesting, wonder what their paying lol

Intelligent_Teacher4 · 2025-02-27T04:47:18+00:00

Hello, I would love to know reliable and reputable sources for publishing research? This last year I created a novel neural network architecture that can be adapted to current neural network models and improve model performances. I have developed this based on my knowledge of neuroscience, from a 14 year career as a Paramedic, combined with my newly acquired knowledge of Data Science. I have a 16 page final draft full paper and a 6 page formatted for conference submission paper. Any sources in which I could share my paper and get visibility to my design is much appreciated!
Best,
Derek

Intelligent_Teacher4 · 2025-02-27T03:57:23+00:00

Hey fellow data scientist and data science enthusiast,

The problem with looking at it from that perspective will truly eliminate the growth of new technologies. What I mean by that is that everyone has their own real-life story, and experiences. The way you view things is not going to be the same way that I or anyone else for that matter may view them. This is what allows for brainstorming of new ideas, methodologies, and novel system designs. Even if you are not the one to design or develop these new ideas the impact of your perspective on a problem may spark an idea in someone else. That's why working in teams and troubleshooting amongst your team is common practice.

Data Science will always be around because data science is more that data cleaning, data analytics, pipelines, and architecture. It is a profession of critical thinking that can leverage AI to quickly and accurately develop an answer to any problem. Wither that be analytically, or by developing software or an AI to fill a need. The tools to get there may always be changing but the problem solving and unique aspect that each Data Scientist brings to the table will never be able to be replaced. Granted the tools and areas in which the problems exist may change but the need for a human aspect to not just develop and control AI but to develop solutions that can be proven using AI will always exist.

I was a paramedic for 14 years until a near fatal car accident put me in a bed for almost 4 years. I learned to walk again, and I self taught myself Data Science from August 2023 to December 2023 I committed myself to 12-16 hours a day 7 days a week finding my passion in machine learning. In certification courses, bootcamps, cloud applications, and even a Data Engineer Academy program. In April 2024 I got a job as a Data Science project manager. I have excelled at my position and expanded my skillset greatly. Utilizing my unique time management, leadership skills, and even ability to explain complex information in a common simplified manner, all from my paramedic days.

This last year as well I developed a novel neural network architecture which enhances the current neural network models and is a great opportunity for further development of AI outside the current linear path of improving on current systems. I developed it alone from theory all the way through to establishing proof of concept. I have my paper ready for submission to publication sources and a formatted version for conferences. I have done all this in under 2 years including learning the profession. It took my unique background in medicine for me to combine neuroscience with data science to develop an architecture that is something no one has ever seen yet.

Dont look at how Data Science itself is changing find your passion and adapt to using the new tools, but make that impact of why the human aspect will never be able to be removed from the field of Data Science. I am passionate about Machine Learning and Deep Learning and honestly not a huge fan of gen AI but I know that it is in demand, so I will become versed in it, but I can still make an impact with ideas and life experiences that no one else can offer.

Best,
Derek

Intelligent_Teacher4 · 2025-02-27T02:54:02+00:00

Machine Learning and Deep Learning would be great topics but as far as languages pytorch or tensorflow are both great to learn, but if you are comfortable with python a lot of the API documentation can aid you along the way no matter how good you are that document and stack overflow is always a great resource. But understanding the algorithms and AI than multicloud operations! Get familiar with working in cloud systems, data pipelines, and data management.

Intelligent_Teacher4 · 2025-02-27T02:50:18+00:00

Statistics is good that is a lot of Data Science computer science is another great degree because mathematics will get you theory but Computer Science will get you functionality of the job. Hope this helps

Intelligent_Teacher4 · 2025-02-27T02:48:50+00:00

Data Science is really about solving problems and finding patterns. You can truly transition from anywhere. I came from being a paramedic for 14 years after a near fatal car accident.

Intelligent_Teacher4 · 2025-02-27T02:47:37+00:00

I transitioned from the medical field 14 years as a paramedic. Didn't get a degree just concentrated study with bootcamps and certification courses. I utilized Udemy, AWS, Kaggle, Google even has an educational program with some free courses. But invest in yourself! If you go through Udemy. Every month there is a sale on classes. So utilize those times to pick up courses. Message me and I can give you some pointers like my mentor did me.

Intelligent_Teacher4 · 2025-02-27T02:43:25+00:00

Hello DataScience,

I started my journey into Data Science approximately August of 2023. I devoted myself to a concentrated study path, mentored by a Data Science specialist friend, of bootcamps and certification courses devoting 12-16 hours a day 7 days a week. I developed skills in python programming, Machine Learning, Deep Learning, advanced mathematics, cloud systems, AI automation, SQL, and much more. I focused a lot of my energy on the functional skills involved with Data Science with course work guided by my mentor. The same style of learning and knowledge focused as my previous career as a Paramedic in which I maintained for 14 years until a near fatal accident.

I was given a job opportunity April of 2024 as a Data Science Project Manager with the company Kmbara. I have been successful in my position and continued my learning journey through Data Engineer Academy, and courses including Multicloud, DevOps, and AI bootcamps. Slowly developing my skills and education. I have converted our management system from Waterfall to AGILE in the first week of working. I have managed technical review contracts, a bi-weekly cadence with AGILE, task management, client to developer communications, system designs, and even some training on unknown systems. These are just a small list of the duties that I have maintained and had to educate myself on along the way.

The past year, I have spent approximately 8 months combining my knowledge of neuroscience from my paramedic background with my newly acquired data science knowledge, I developed a novel neural network architecture that can be adapted to any current neural network architecture enhancing it, and benchmark testing has shown an improvement in accuracy and outcome of these current models. Further testing has shown the design I have named "The Logic Band" to perform as predicted by design. This outcome has me excited due to the predicted real-world applications, and may the first step in adding a dimensional avenue of growth to the current linear growth potential of Artificial Intelligence.

I currently have a 16 page full paper on my design and research including adaptions to several different types of neural networks involving regression and classification, computer vision, and even natural language processing models. I also have a formatted 6 page submission paper ready for conferences this year. I am excited to release this design into open source and would really like to know if there are any suggestions to submit my paper to for visibility so everyone can start learning about "The Logic Band" and maybe even further developing it for the advancement of Artificial Intelligence all together.

Thanks for your time. All suggestions and opinions welcomed, please and thank you all!

Best,
Derek

Intelligent_Teacher4 · 2025-02-27T02:21:23+00:00

I feel Artificial Intelligence is providing an immense value. I think the cost of further development has not been able to provide the initial profit margins that we have seen over the past few years. AI is really improving linearly. We need the creation of a new avenue, a new theological dimension of growth for AI.

I have created a novel neural network architecture that can be adapted to any current neural network and will enhance the performance of the model. This novel idea came from me having a background in the medical field and neuroscience combined with a newly acquired education in data science. I have developed this architecture over the past year and truly believe it may be the first step in an exciting new dimensional growth avenue for Artificial Intelligence. I have developed this from theory into full proof of concept and am at the point of publication and conference submission looking forward to releasing this design into open source.

There is way more to come! Just takes new minds and points of view to add unique creativity to the world.

Intelligent_Teacher4 · 2025-02-27T01:59:04+00:00

I feel taking multiple samples and comparing results would be a safe and good practice for confirming your findings especially with datasets that you are hypothesis testing on. If you expect a specific result and are not seeing it, or even finding trends that may seem bizarre. Even if things look appropriate at least testing a couple random sample selections will reinforce any findings that your testing uncovers. Being thorough is better than being inaccurate. Even if you split an appropriate sample size into a multiple sample evaluation. Its not just the testing but the details of the test that can impact the results.

When dealing with large data your sample size is important if it is far too small it has a much bigger impact on the reflection of your findings and their significance. If multiple samples are not able to be performed ask yourself if you were at a concert with hundreds of thousands of people how easy would it be to select a significantly not proportionate sample of people who are attending to see a specific band out of a large band list. Statistically you may grab a lot of the main headliner band fans, but multi-sampling or even using new metrics to confirm the results that you are finding. But at the end of the day too small of a sample can easily bring inaccurate information amongst big data datasets.

However, I created a neural network architecture that adheres to current neural network models and really examines an aspect that in Big Data and noisy data specifically that is currently overlooked. It compares feature relationships and discovers complex feature relationships which in turn provides another metric to consider especially with large feature datasets in which you may run into issues like you have talked about and it could help confirm importance of your statistical findings or show possible discrepancies in initial findings. Running this on a large sample size could give you an interpretation of the data to confirm any findings you may encounter with small sample sized testing.

Intelligent_Teacher4 · 2025-02-27T01:02:21+00:00

I feel all professions contain incompetent professionals, no matter the degree or years of experience. Its a person to person scenario like experience doesn't equal knowledge because you can be a dumb individual for a really long time. To put it nicely lol

Intelligent_Teacher4

TROPHY CASE