Predictive modeling: Linear Regression. Machine Learning vs Data Science
Linear regression is the most popular supervised learning technique or the most popular data science technique in general.
Here we would take a deeper dive on Linear Regression learnings.
Also, we would look at how Data Science has commonalities and differences from Machine Learning
Open Source Hugging face GPT (HuggingChat) vs ChatGPT!
So hugging face just launched an open source competitor, always a good thing! It using the Model: OpenAssistant/oasst-sft-6-llama-30b ·
https://huggingface.co/chat/conversation/644be6523f6f5333935d03a0
Quick comparison continuing on my previous post of ChatGPT vs Auto GPT!
AutoGPT vs ChatGPT
Today i spent sometime setting up AutoGPT on my mac. It took about 30 minutes following a youtube video… had python already installed, but had to install xcode for agreeing to an agreement and visual code for better file management and editing..and rest was using the Mac terminal commands. Very easy to set up. it needed open API key to get started. I have some free credits but if i run out of it, i will have to enter my billing details.
ChatGPT a day
I have used to learn concepts of Data science and Python.
I have used it to generate a quiz on AI and itself and used that in office for leadership connects and practice AHMs.
I have used prompts from it to generate images using mid-journey.
AI in Healthcare
You become a doctor or you become a programmer, not both. AI is changing that. Emma shared interested insights into how she wanted to be on technical side but had primary subjects in medical field, and then when a moment came to utilise AI she jumped into it to explore her love for technology again. She has done phenomenal work in researching the usage of AI on various areas, creating and experimenting with different models, doing Phd and also a teacher in this space.
Reducing the noise
Our mind cannot processes a ton of information at the same time very effectively to decide if a lot of it is redundant. We need good quality information or try to peel the layers of information we get when dealing with our work or relations, then infer something, then think again, then infer something better and then decide.
Normal Distribution
As per Central Limit Theorem, if you take a large enough data set - it tends to always follow normal distribution in statistical terms. Is this why we tend to use bell curve in appraisal systems?