How to Become a Data Scientist
Organizations globally are increasingly relying on data to make their business processes more efficient, reach their customers more effectively, and make better decisions. Being a data scientist can be an extremely rewarding career, where you help these organizations gain insights from their data and make the decisions that really matter. But people often want to […]
Top 10 Pandas Methods You Haven’t Heard of
If you’re a data scientist, you’ve probably heard of Pandas. It’s one of the most popular open-source data analysis libraries out there. But did you know that Pandas has a ton of hidden features? In this blog post, we’ll discuss 10 Pandas methods that you haven’t heard of. These methods can help you do everything […]
How to Build a Data Analyst Portfolio
If you’re looking to start a career in data science, one of the most important things you need to do is build a strong portfolio. A data analyst portfolio will showcase your skills and experience, and it will help you stand out from the competition. In this blog post, we’ll discuss how to build a […]
Top 10 R Data Science Libraries
While Python is arguably the most popular programming language used in Data Science, there are still some areas where R is better. For example, R is generally better than Python for building statistical models. Likewise, R also simplifies the process of creating graphics and data visualizations. As such, R remains a valuable tool in every […]
Visualizing Prediction Markets with Kalshi and Python
Visualizing Prediction Markets with Python and Kalshi¶ In this blog post we’ll explore Prediction Markets using Kalshi. What is Kalshi?¶ Kalshi is a predictions market, regulated by the Commodity Futures Trading Commission (CFTC) where you can buy event contracts based on future outcomes for certain events, such as the number of COVID cases […]
Understanding Random Forest Algorithm
The Random Forest algorithm is a machine learning technique that is used to predict the outcomes of events. It is a type of ensemble learning, which means that it combines the predictions of multiple models in order to produce a better prediction. A Random Forest algorithm is commonly used for classification and regression tasks. In […]
How to interpret box plots
Box plots are a great way to visualize your data. They can help you see the distribution of your data, as well as any outliers that may be present. In this article, we will show you how to interpret box plots, and give some examples of how they can be used in machine learning applications. […]
Understanding Boosted Trees Algorithms
There has been a recent resurgence of interest in Boosted Trees Algorithms. This is due to the success of machine learning algorithms in general, and the realization that boosted trees are a very powerful tool for solving many problems. In this article, we will discuss what boosted trees are, and how they work. We will […]
How to Convert A .py Script into A .exe File
Picture this: you’ve just finished creating a fantastic Python program and intend to let the world see it. You then send your friend a directory containing all your scripts and encourage them to try it out. Only first, they must install Python and then run the program via the IDLE shell or the command line. […]
Visualizing Historical Yield Curves with Plotly and Python
In this blog post we’ll explore visualizing the Yield Curve through a cool 3D Surface Plot, since we’ll be exploring 3 dimensions of data: the rate yields, the publication date, and the rate periods. Grabbing Yield Curve for 2022¶ We can use the pandas library to directly read the HTML table from the […]