LibGuides: ANA499B v1: Module 2 Resources

Module 2 Required Resources

The Craft of Scientific Presentations
Alley, M. (2013). The craft of scientific presentations (2nd ed.). Springer.
- Refresh your use of the assertion evidence method by reviewing chapters 3 and 4, and all of the critical error subsections within.
  - Chapter 3: Structure – The Strategy You Choose : Critical errors are discussed, including trying to cover too much, losing the audience from the start. Losing the audience on the trail and not anticipating the audience’s bias.
  - Chapter 4: Visual Aids – Your Supporting Cast: Critical errors are discussed, including following the PowerPoint defaults and common practices.
5 Regression Algorithms You Should Know
Analytics Vidhya. (2021, May 18). 5 regression algorithms you should know: Introductory guide.
- In machine learning, regression algorithms play a pivotal role in modeling the relationship between a dependent variable and one or more independent variables. These powerful techniques enable data scientists and analysts to make accurate predictions of numerical values, shedding light on intricate patterns and trends within datasets.
What is Classification in Machine Learning?
IBM. (n.d.). What is classification in machine learning?
- Classification in machine learning is a predictive modeling process by which machine learning models use classification algorithms to predict the correct label for input data.
Clustering in Machine Learning: 5 Essential Clustering Algorithms
DataCamp. (2023, July 18). Clustering in machine learning: 5 essential clustering algorithms.
- Clustering is an unsupervised machine learning technique with a lot of applications in the areas of pattern recognition, image analysis, customer analytics, market segmentation, social network analysis, and more.
Association Rule Mining in Python Tutorial
DataCamp. (2023, October 10). Association rule mining in Python tutorial.
- Association rule mining is a technique used to uncover hidden relationships between variables in large datasets. It is a popular method in data mining and machine learning and has a wide range of applications in various fields, such as market basket analysis, customer segmentation, and fraud detection.
The Complete Guide to Time Series Models
Built In. (n.d.). The complete guide to time series models.
- A time series model is a set of data points ordered in time, where time is the independent variable. These models are used to analyze and forecast the future.