I am collecting my notes as I study to become a cloud engineer with a focus on databases.
I am a bit lost in dataframes right now, so I decided to take a step back and review compound data types. A very tricky stumbling block for me occurred when I did a simple thing: This is list a: [‘a’, ‘b’, ‘c’, ‘d’, ‘e’]This is list b: [‘a’, ‘b’, ‘c’, ‘d’, ‘e’] (output from […]
I’ve been using Python Pandas to analyze the data I recently scraped from BoardGameGeek. I have used lists and dataframes, but this experience showed me how much I have to learn. The official documentation is a treasure trove of information, but can be difficult to understand. One of the first obstacles is figuring out where […]
While working on my first web scraping program in Python3, I wanted to pause between each pull from the target site. Here is an example of how to pause Python code mid-execution: Here is an alternate form for accessing the random and time libraries: Both of these forms produce the same output: These examples show […]
This last week I participated in my first hackathon. What a crazy ride! Women Hack the Crisis was hosted by The Expat Woman. We called ourselves TeamWHOW (Women Helping Other Women). We chose to develop “BEBO the Benefits Bot.” It was pure serendipity that I chanced upon a request for team members on the Women […]
I’ve been busy with Chuck Severance’s Python 4 Everybody specialization at Cousera. One of my favorite homework assignments so far is the Page Rank web crawler. I modified the original spider to only crawl Wikipedia. Each web starts at the poet’s wiki page. After randomly crawling 100 pages, the code ranks the sites in the […]
The final part of the basic supervised machine learning trinity is the gradient descent algorithm. Given a hypothesis and a cost function, this algorithm iterates through different values of ‘theta,’ (remember this is a parameter set), to find something called the local optima for a particular data set. Right, but that explanation is […]
I decided to look into the world of blockchains, because, regardless of what happens to bitcoin and other cryptocurrencies, blockchains are here to stay. My interest is in blockchains as ledgers, not cryptocurrency. A ledger is just a list of transactions. Blockchains are ledgers that use a decentralized model for verification. The decentralized model is […]
Time to introduce a vital concept in machine learning: parameters. Previously, I talked about ‘thetaZero’ and ‘thetaOne’ and their use in the linear hypothesis algorithm. The proper term for them is ‘parameters’ and they belong to a set ‘theta’ commonly notated as It is best to think of ‘theta’ as where ‘n” is […]
I call this a cost function rather than the cost function because one cost function does not fit all. Cost functions vary depending on the kind of data set or machine learning model. For the purposes of machine learning, cost functions become the algorithms that measure the performance of hypotheses. This equation comes […]
The very first formula I learned in machine learning (and the first time I tried writing in LaTeX!) So pretty cool, but what does it mean? This is an example of a univariate hypothesis. ‘Univariate’ is a fancy way of saying that I have one variable (let’s call it ‘x’ for now) that […]
