HW5

Thoughts On Week Five and Other Things

1) Prediction Markets

PredictIt

A good site that predicts election outcomes. This is kinda relevant with this being an election year and we can watch it play out in realtime.

Metaculus

Metaculus questions the occurrence of future events based on different timescales and variables. I think the site is an interesting read. 

2) What’s wrong with prediction markets?

A big reason why prediction markets could be wrong is just the amount of variables that need to be accounted for. It’s nearly impossible to accurately predict down to the letter what the future holds and what impact that could have on the markets. 

3) The universe is not a friendly place!

I think it’s important to do good things but do them without their expectation that the universe does not owe you a thing. In my opinion, this is the lesson that should be learned, you can do everything right and still have nothing and have bad things happen to you. People should do that “right” thing because they want to and it makes them a better person. A couple books that I think are more accurate to the human condition that helped me are.

The Universe Doesn’t Give a Flying F**k About You

The Subtle Art of Not Giving a F*ck: A Counterintuitive Approach to Living a Good Life

4) Will my project help my future? 

The scope of my project encompasses everything I do on a day to day basis in my current career and can have an impact on my future and career. Machine learning and AI are a big deal in the tech industries right now anything that helps me gain experience within that skillset is great. I don't need to build the next big thing just work on getting a better understanding of how the technology works and how it can be incorporated into everyday life.

Other things I hope to gain by working on this project is a better understanding of coding in general, as well as critical thinking and attention to detail. Seeing the pieces and how the software works and fits together will strengthen my skill set and make me more marketable to potential future employers. 

5) Resources for me and mine!

https://www.geeksforgeeks.org/how-to-start-learning-machine-learning/

This site just contains information on how to get started with machine learning. The site covers terminology and technologies used. 

https://elitedatascience.com/learn-machine-learning

A how-to guide for the self-starter on machine learning. 

https://machinelearningmastery.com/machine-learning-in-python-step-by-step/

This site provides a step-by-step project in python. This site would be good for getting as the baseline project started. 

https://blog.usejournal.com/how-i-built-and-deployed-my-first-machine-learning-project-4c75d1effe4e

An interesting read was written by someone about their first machine learning project. This is good for getting inside I might not think of on my own. 

https://elitedatascience.com/machine-learning-projects-for-beginners

We all need to start somewhere. This gives some good starting projects for people just getting into machine learning. 

https://web.mit.edu/tslvr/www/lessons_two_years.html

MIT provides a lot of free resources for people who are interested in science and tech as well as auditing classes for free. This site is a lesson from someone in working with AI. 

https://www.freecodecamp.org/news/every-single-machine-learning-course-on-the-internet-ranked-by-your-reviews-3c4a7b8026c0/

You don't know what you don't know! This site is a list of machine learning course online in case I get stuck and need more resources. 

https://www.scipy.org/

I will most likely be writing this in python, more specifically SciPy. This is the home page for SciPy and includes all the packages I might need. 

6) Do

Succeeded

7) Monitor

Worked

8) Accountability

The accountability step was good for going back through and making sure you were being specific with your goals and initial in your actions to get there.