Train in Data Reviews 

Thorough yet gentle introduction to important aspects of time-series feature engineering.

Excellent and practical book. Easy to read and very interesting

I really enjoyed the course Feature Engineering for Time Series.
It combines theoretical knowledge with practical implementation using different libraries.

I love feature-engine and its versatility for a number of daily needs.Thanks Sole and Train in Data for getting me to know your library and for developing such great courses and material.I was not able to find such a juice of theory and practice as in your courses. Waiting for the next one :)

I have gone through the courses for feature engineering and selection and they have been a great overview of techniques that they can be used for modeling. The presentation is clear and concise.

I'm a data scientist and have taken the following courses on Udemy from Train in Data [lecturer: Soledad Galli]:
- Feature Selection for Machine Learning
- Machine Learning with Imbalanced Data
- Feature Engineering for Machine Learning

Following an explanation of Why this data preprocessing operation was needed, there is a demonstration of How to do it in Python. Every video has it's documented Python notebook. In addition to the operation itself the code includes EDA/visualization of the data before and after and sometimes even a snippet of ML to show how the data preparation affected the result. I'm retaking the course on Feature Engineering since it has now almost doubled in size. Especially nice are the Python "one liners" which show how to do complex computation on a Pandas data frame elegantly and concisely.

The quality and depth of the lecture materials are unparalleled. The dedication and meticulous effort put into crafting these state-of-the-art resources is evident. My commendations for such an exemplary job.

Great course! A good and correct mix of theory and practice. I believe very complete course on feature engineering for time series. The course materials are also very useful and helpful.

Insightful and relevant content about Machine Learning..

This Data Bites email tips is very useful for begineers like me in Data Science field.

Things like Feature Engineering and Selection.

The most important part of a data science or machine learning project is feature engineering. So I have learnt lot of things from here. It's an amazing experience for me. I hope more things I will explore from here in future.

Trainindata is a leading platform to learn about data science. Soledad will help students to excel. I have no hesitation to recommend trainindata to aspiring data scientists as they will get bang for buck.

The topics are presented in a clear and concise manner, with each section providing helpful examples to illustrate the concepts and help you apply what you are learning.

I bought one of her courses from Uemy and it was comprehensive enough to absorb. I love the additional resources provided.It is my pleasure to buy more of her courses

Amazing Teaching. I thought the Feature Engineering course was an excellent resource for anyone who wants to learn more about this critical topic. The course was well-organized and informative, and the instructor did a great job of explaining the concepts in a clear and concise way. I highly recommend this course to anyone interested in improving their machine-learning skills.

I am newbie with forecasting but with that course I look like a senior forecasting guy when I talk with my team about this course! I'll practice a lot with data from my work but this course has a high level of knowledge. Thanks team

What i have been so far, its looks very interesting and challenging too as i am not a pure Machine Learning Expert. Currently, my focus is for the time series forecasting and the things which circulate around it.Since the course is based on Feature Engineering for Machine Learning models, its good to know what are the essential ingredients which makes the forecasting possible to churn out the numbers what the business is looking for it. Its a journey which so far is going good and need to re-iterate myself what has been discussed so far by practising again and again. Further, if the explanation can be extended more with the help of more examples and exercises that would be good.

The explanations are very clear. I like the fact that the new features are shown on the same data sets that were used in the first demo.
It could be better if there was a code assignment after every big chapter/section, so we can practice the techniques learned.

Very concise, insightful and up-to-date course. The code examples are also of high quality and very useful. I am a big fan of Train in Data.