Understand Classification Performance Metrics
2018-10-19 00:00:00 +0000
Better understand how to access your classification models.
Machine Learning: Bias VS. Variance
2018-10-11 00:00:00 +0000
The difference between bias and variance in machine learning.
Books: Wait, people used to do this?
2018-07-09 00:00:00 +0000
Better understand how to access your classification models.
These Weapons Will Mathematically KILL You
2018-04-07 00:00:00 +0000
The shortcoming of machine learning models.
Stock Analysis
2017-12-25 04:00:00 +0000
We will be answering the following questions along the way 1. What was the change in price of the stock over time? 2. What was the daily return of the stock on average? 3. What was the moving average of the various stocks? 4. What was the correlation between different stocks closing prices? 4. What was the correlation between different stocks daily returns? 5. How much value do we put at risk by investing in a particular stock? 6. How can we attempt to predict future stock behavior?
Election Analysis
2017-12-25 04:00:00 +0000
In this project we will analyze two datasets. The first data set will be the results of political polls. We will analyze this aggregated poll data and answer some questions: 1. Who was being polled and what was their party affiliation? 2. Did the poll results favor Trump or Clinton? 3. How do undecided voters effect the poll? 4. Can we account for the undecided voters? 5. How did voter sentiment change over time? 6. Can we see an effect in the polls from the debates?
Boston Analysis
2017-12-25 04:00:00 +0000
The project is used to analyze the prices of houses in Boston. The model uses will be used is a linear regression and decision tree regressors. Provides an insight on how decision tree are used for continuous output and not just a classification problem.
False Positives & False Negatives
2017-12-05 00:00:00 +0000
Information on false positives and false negatives with a conceptual framework.
Specificity & Sensitivity
2017-12-04 00:00:00 +0000
Information on specificity & sensitivity (true positive rate and true negative rate).
Linear Regression 101
2017-12-03 00:00:00 +0000
In the simplest form, it is a line that passes, or plane, or any higher dimension figure through the points that minimizes the least squares. While this might sound abstract or weird, I will try to clarify this concept by the end of this post.
Impossible List
2017-12-03 00:00:00 +0000
My IMPOSSIBLE LIST (inspired by CollegeInfoGeek)
Confidence VS. Prediction
2017-12-02 00:00:00 +0000
Understanding confidence and prediction interval (simple).
Bias VS. Variance
2017-12-01 04:00:00 +0000
Understanding bias and variance tradeoff. This is important to understand with figuring out the models to apply.
The 5 Books That Will Help You Never Make a Mistake
2017-08-04 00:00:00 +0000
Cliche? Sort of, but I’ll explore this idea differently than most. Instead of looking at it how you garner negative thoughts that can be detrimental to our mental health, I want to explore your mundane thoughts. **Thoughts that on the surface, appear harmless. Moreover, thoughts that stem from our biases.
5 Books that Helped Me Understand Your Struggles
2017-07-25 00:00:00 +0000
Now to the fun part. As an avid book reader, I have come across some real good books. Some of the good books helped me break biases and gain fresh perspectives. Hence, I created a list of 5 books that I think will greatly help widen YOUR experience.
Pomodoro Technique, version 4.u
2017-07-24 00:00:00 +0000
Use the Pomodoro technique to be more efficient.