While checking the performance of regression models, the fundamental methods are r-squared and adjusted r-squared.
This question is ubiquitous in data scientist interviews too. The adjusted r-squared has an added advantage over the r-squared.
So learn the key differences between the r-squared and adjusted r-squared with advertising vs sales growth case study.
As a fresher, it’s very hard to get the data scientist job. The same applies to the people who are changing from other domains or technology to the data science field.
But if we follow a strategy to prepare to learn the data science field’s required skill set. We can undoubtedly get the first job as a data scientist.
This article helps you achieve this by providing 6 stage strategy to get your entry-level job as a data scientist.
In the article, we provided completely free resources (zero cost) to become a data scientist. In other words, the article’s intention shows how you can use the strategy and the free resources to become a data scientist.
If we miss any free and valuable resource, do let us know, we will include those in the article.
Activation functions are the building blocks for simple neural networks and the complex deep learning network architectures.
People tend to use these activation functions like try and error type while building deep learning networks.
But if you learn the properties of these activation function, you will know which activation function has to use where.
The article listed the popular activation functions used in the industry. If we miss any, do let us know, we would love to include that in the article.