tips and tricks

1. Docker

1. Commands: Quick Reminder of Docker Commands.

2. ASP.net

W#

1. Background services with Hangfire: An easy way to perform background processing with .NET.
2. Performance C#: Perfomance comparison between List x enumerable using for, foreach and linq. What are the bets for the best performance?
3. UNIT OF WORK: Implementation of the repository standard with Unit of Work.
4. Linq: concept and examples of Linq to facilitate understanding.

Web app

1. Syntax Razor for ASP.net Core: render C# to HTML through the Razor syntax.
2. HTML Helpers x Tag Helpers: Compare the use of HTML Helpers x Holpers tag and learn how to create custom tags.

Openid and Oauth 2.0

1. IdentityServer4: Framework that implements the free Openid and Oauth 2.0 protocols, Open Source and available for ASP.net Core.

3. Flutter

1. Package Get: Package Get for Flutter with state management, dependence and navigation injection resources.
2. Unit and Widget Tests: Flutter project with demonstration of unit tests and widget tests.
3. Animation List of Images: Image List, similar to Instagram, with an animation of like in the double user touch.

4. Angular

1. Dynamic Forms: Angular project with the objective of simulating the creation of form dynamically.

5. Python, Pandas and Machine Learning

Python

1. DATETIME: Manipulate dates and hours.
2. File Organizer: Organize the files of a directory by type.
3. Decorators: Add features to an existing method without changing its structure.

Pandas

1. pandas.core.groupby.groupby.cumcount (): Create a self -column column based on a group of columns.
2. pandas.cut (): Convert numerical data into categorical data.
3. pandas.dataframe.diff (): Calculate the value difference between each line of a dataframe.
4. pandas.dataframe.unstack (): converts indices into columns.
5. pandas.series.st.Contains (): See whether a regular value or expression is contained within a series.
6. pandas.melt (): Convert the elements of a list into several lines in Dataframe.
7. pandas.dataframe.explode (): Available from version 0.25, convert the elements of a list into several lines in Dataframe.
8. pandas.api.types.categoricaldtype: define an order for categorical variables.

Machine Learning

1. Categorical Variables: Know 3 techniques to work with variable categorical.
2. Missing Values: Meet 3 techniques for working with missing values.
3. Sklearn.pipeline.Pipeline: Group the pre-processing and data modeling steps.
4. sklearn.model_selection.cross_val_score: Run the modeling process in different data subsets to obtain various model quality measurements.

Challenges

1. Kaggle Credit Card - Balance forecast: This notebook presents a model capable of predicting credit card balance according to a series of user characteristics.
2. Kaggle Credit Card - Customer Segmentation: This case study requires developing a model to identify customer segmentations in order to define a marketing strategy.