More from Brendan

Artificial Intelligence

Demystifying Machine Learning: What AI Can Do for You

By demystifying machine learning, we unveil a world of possibilities where AI becomes not just a buzzword, but a tangible tool for enhancing productivity, efficiency, and innovation.
Tech Trends

Intro to Predictive Modeling: A Guide to Building Your First Machine Learning Model

Predictive modeling in data science involves using statistical algorithms and machine learning techniques to build models that predict future outcomes or behaviors based on historical data. It encompasses various steps, including data preprocessing, feature selection, model training, evaluation, and deployment.
Tech Trends

Introduction to Natural Language Processing (NLP) in Data Science

Natural Language Processing (NLP) encompasses a variety of techniques designed to enable computers to understand and process human languages. In this post you’ll learn about NLP applications like text classification and sentiment analysis, plus NLP techniques like tokenization and stemming.
Tech Trends

Decoding Data Jargon: Your Key to Understanding Data Science Terms

You should only use data science terms such as mean, median, standard deviation, correlation, and hypothesis testing if you are confident in being able to explain them. This post walks readers through explanations of some of the most common data science terms.
Tech Trends

Using Scikit-Learn for Machine Learning in Python

Data scientists using Python must be comfortable and proficient in using scikit-learn, which is why Flatiron School’s Data Science Bootcamp emphasizes it throughout its curriculum.
Tech Trends

Rejecting the Null Hypothesis Using Confidence Intervals

After a discussion on the two primary methods of statistical inference, viz. hypothesis tests and confidence intervals, it is shown that these two methods are actually equivalent.
Artificial Intelligence

Hyperbolic Tangent Activation Function for Neural Networks

Activation functions play an important role in neural networks and deep learning algorithms. A common activation function is the hyperbolic tangent function, which is like the trigonometric tangent function, but defined using a hyperbola rather than a circle.
Artificial Intelligence

Why Do We Need Statistics for Data Science?

Data science needs statistics not only for descriptive and inferential statistics, but also for the statistical learning techniques of artificial intelligence.
Career Advice

Learning Mathematics and Statistics for Data Science

Data Science is a rapidly growing field, but as prospective students consider data science, they often have trepidation about the mathematics and statistics involved. Learn why we need mathematics for data science.