The best way to start learning TIMi is to follow these 8 Youtube training videos about Anatella:

1. How to install TIMi/Anatella on a computer?
2. Your first Anatella data transformation
3. Let’s use a row-filter box!
4. Aggregate, sort and plot data
5. The Anatella cache system
6. How to put your Anatella graphs in production
7. Anatella’s best practices
8. The most common Anatella boxes

Once you have followed the above 8 videos about Anatella, you’ll be able to do almost any data-related activities such as: collecting data, importing data, transforming data, data wrangling, data cleaning, plotting data, exporting data to other BI tools or to cloud services, feature engineering, etc.

 
We strongly encourage you to follow the above 8 videos about Anatella because they’ll greatly help you in learning the “TIMi Suite”. The other videos here below are only useful if you have very specific needs: i.e. if you have a machine learning or clustering exercise to do.
 

Within Anatella, all the open source libraries to create predictive models to perform machine learning activities are directly available, just in a few mouse clicks. But, if you want to engage in the most advanced machine learning exercices, you’ll need an Automated-Machine-Learning tool such as “TIMi Modeler”. Here are a few Youtube video tutorials about Modeler:

1. A short introduction to predictive modeling and how to create your first predictive model with Modeler
2. How to use Modeler directly from within Anatella to automatically re-create new model on-the-fly each week?
3. Solving a very advanced Text Mining problem with TIMi Modeler

Always within Anatella, all the open source libraries to segment/cluster your datasets are directly available, just in a few mouse clicks. But, if you want to engage in the most advanced clustering exercices, you’ll need an advanced 3D segmentation tool such as “Stardust”. Here are a few Youtube video tutorials about Stardust:

1. Segmentation theory: Theoretical Introduction to the PCA technique – part 1.
2. Segmentation theory: Theoretical Introduction to the PCA technique – part 2
3. A demonstration of the multivariate segmentation engine of Stardust – part 1.
4. A demonstration of the multivariate segmentation engine of Stardust – part 2.

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