Category: Data Science

Data Science, Machine Learning, Python Basics

Machine Learning with Python: Linear Regression

Introduction In this blog post, we’ll be exploring Linear Regression in Machine Learning with Python.  There are many potential applications for linear regression, especially for your business, including: Sales forecasting: Linear regression can be used to predict future sales based on historical data, such as product pricing, marketing expenses, and consumer demographics. Inventory management: Linear […]

Data Science, Machine Learning

7 Regression Algorithms Used in Python for Machine Learning

Regression analysis is a commonly used statistical technique for predicting the relationship between a dependent variable and one or more independent variables. In the field of machine learning, regression algorithms are used to make predictions about continuous variables, such as housing prices, student scores, or medical outcomes. Python, being one of the most widely used […]

Data Science, Python Basics

Analyzing Taylor Swift’s Songs with Python

Analyzing Taylor Swift’s Songs¶ To celebrate Taylor’s new album which has 10 of the top 10 Billboard charts (first time to ever happen), let’s explore Taylor’s discography with the Spotify API. Get credentials from Spotify API¶ Go to your Spotify Dashboard at https://developer.spotify.com/dashboard/ and create a new application, then grab the Client ID and Client […]

Data Science, Machine Learning

Self Supervised Learning

Deep Learning without labels – Self-Supervised Learning¶ In this blog post we’ll discuss Self-Supervised Learning! Classical supervised learning suffers from four main problems: Fully labelled datasets are expensive or not available at all. There is a large amount of unlabeled datasets which cannot be leveraged by Supervised Learning. Difficuly in creating One-Shot or Few-Shot systems, […]

Data Science, Tutorials

Analyzing Senate Stock Trades

Analyzing Stock Market Activity of US Senators with Python¶ In 2012, a law called ” Stop Trading on Congressional Knowledge (STOCK) Act of 2012″ was passed, which prohibits the use of non-public information for private profit, including insider trading by members of Congress and other government employees. This law however did not completely ban stock, […]

Data Science

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 […]

Data Science

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 […]

Data Science, R

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 […]

Data Science, Tutorials

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 in the […]

Data Science, Machine Learning

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. […]

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