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https://github.com/solegalli/solegalli


https://github.com/solegalli/solegalli

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README 

        
# Hi! I'm Sole (Soledad Galli) 👋



Hey there! 👋 I'm Sole, a seasoned data scientist, published author, and machine learning 

instructor with a passion for pushing the boundaries of what's possible in the world of data science. ✨



In my journey that kicked off in 2015, I've lent my expertise to finance and insurance companies. Here, I 

honed my skills in crafting robust machine learning models, tackling challenges such as insurance claim 

assessments, credit risk evaluations, and fraud prevention.



In 2017, I pioneered my first online course, **'Feature Engineering for Machine Learning.'** Recognizing a 

gap in resources at the time, I've since expanded my course offerings, delving into diverse aspects of machine 

learning. Additionally, I've given life to an open-source Python gem: [**Feature-engine**](https://github.com/feature-engine/feature_engine). 🚀



Currently, I'm pouring my energy into advancing [**Feature-engine**](https://github.com/feature-engine/feature_engine) 

and creating new, impactful [**courses on machine learning**](https://www.trainindata.com).



You'll often find me sharing insights about Feature-engine and the broader machine learning landscape through blogs, 

talks, and podcasts. 



If you discover that [**Feature-engine**](https://github.com/feature-engine/feature_engine) brings value to your work 

or learning journey, consider [sponsoring my efforts](https://github.com/sponsors/feature-engine) or enrolling in

my [**courses**](https://www.trainindata.com). 



Your support goes a long way in fueling the growth of valuable resources and impactful courses for the community.



Excited to connect, collaborate, and learn together! 🌟"



[](https://www.trainindata.com)



## Online Courses



Check out the courses that we teach. Courses are up to date and work with the latest Python library releases!



| Courses | What you will learn |

|---|---|

| [**Feature engineering for machine learning**](https://courses.trainindata.com/p/feature-engineering-for-machine-learning) |  Learn to create new features, impute missing data, encode categorical variables, transform and discretize features and much more. |

| [**Feature selection for machine learning**](https://courses.trainindata.com/p/feature-selection-for-machine-learning) |  Learn to select features using wrapper, filter, embedded and hybrid methods, and build simpler and reliable models. |

| [**Hyperparameter optimization for machine learning**](https://courses.trainindata.com/p/hyperparameter-optimization-for-machine-learning) |  Learn about grid and random search, Bayesian Optimization, Multi-fidelity models, Optuna, Hyperopt, Scikit-Optimize and more. |

| [**Machine learning with imbalanced data**](https://courses.trainindata.com/p/machine-learning-with-imbalanced-data) |  Learn about under- and over-sampling, ensemble and cost-sensitive methods and improve the performance of models trained on imbalanced data. |

| [**Feature engineering for time series forecasting**](https://www.courses.trainindata.com/p/feature-engineering-for-forecasting) |  Learn to create lag and window features, impute data in time series, encode categorical variabes and much more, specifically for forecasting. |

| [**Forecasting with Machine Learning**](https://www.trainindata.com/p/forecasting-with-machine-learning) |  Learn to perform time series forecasting with machine learning models like linear regression, random forests and xgboost. |

| [**Machine Learning Interpretability**](https://www.courses.trainindata.com/p/machine-learning-interpretability) |  Learn interpret and explain white-box and black-box models both globally and locally, including methods LIME, SHAP, and more. |



## Books



Discover plenty of feature engineering and feature selection techniques in my books, where I seamlessly integrate

plenty of methods using readily available Python libraries.



| Books | Summary |

|---|---|

| [**Python feature engineering Cookbook, third edition**](https://www.packtpub.com/en-us/product/python-feature-engineering-cookbook-9781835883587) |  Over 70 code recipes to implement feature engineering in tabular, transactional, time series and text data. |

| [**Feature selection in machine learning with Python**](https://leanpub.com/feature-selection-in-machine-learning/) |  Over 20 methods to select the most predictive features and build simpler, faster, and more reliable machine learning models. |



## Open-source



I actively contribute to open-source libraries as part of my commitment to fostering collaborative innovation and enhancing accessibility in the realm of data science and machine learning.



| Library | About | Role | Sponsor us |

|---|---|---|---|

| [**Feature-engine**](https://github.com/feature-engine/feature_engine) | Multiple transformers for missind data imputation, categorical encoding, variable transformation and discretization, feature creation and more. | Developer and maintainer | [Sponsor me](https://github.com/sponsors/feature-engine) |

| [**tsfresh**](https://tsfresh.readthedocs.io/en/latest/) | Automatically create features for time series classification | One time contributor to expand documentation. |  |

| [**imbalanced-learn**](https://imbalanced-learn.org/stable/) | Tools for under- and over-sampling and dealing with imbalanced data | Multiple PRs to improve documentation. |  |



## Follow me



Stay connected and follow me across these platforms to stay updated on the latest in data science and machine learning:



| Media | Summary |

|---|---|

| [Train in Data](https://www.trainindata.com/) | Enroll in our courses and books |

| [YouTube](https://www.youtube.com/@TraininData) | I post about data science, machine learning and how to become a data scientist.|

| [Newsletter](https://www.trainindata.com/p/data-bites) | I talk about data science, machine learning and how to become a data scientist. |

| [LinkedIn](https://linkedin.com/in/soledad-galli) | I talk about data science, machine learning and how to become a data scientist. |

| [Twitter](https://twitter.com/Soledad_Galli) | I tweet about data science, machine learning and how to become a data scientist.|

| [Facebook](https://facebook.com/trainindata) | I talk about data science, machine learning and how to become a data scientist.|

| [Blog](https://www.blog.trainindata.com/) | I write about data science, machine learning, feature engineering and selection and more. |




  



## Sponsor me



| :zap:        [Sponsor me](https://github.com/sponsors/solegalli)   |

|--------------------------------------------------------------------|




  



## Github Stats  

  




  



![Profile views counter](https://komarev.com/ghpvc/?username=solegalli&&style=flat-square)  

  





**That's it! I hope to see you around.**