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Mario Filho English
Brazil
เข้าร่วมเมื่อ 7 ก.ค. 2021
I am a Machine Learning (ML) Expert & Data Scientist with 7+ years of experience helping companies globally.
Kaggle Grandmaster who achieved multiple 1st place finishes in global Kaggle competitions, and top global rank at 12th of 50,000+
Content Consultant for Applied Data Science with Venture Applications: Data-X (INDENG 135/235) at University of California, Berkeley
Site: forecastegy.com
Follow me on Twitter: mariofilhoml
Kaggle profile: www.kaggle.com/mariofilho
LinkedIn: linkedin.com/in/mariofilho/
🤖 Building machine learning systems since 2014
🏆 2x Prize Winner Kaggle Competitions Grandmaster
📊 Former Lead Data Scientist @ Upwork
🎓 @UCBerkeley Data-X Consultant
Kaggle Grandmaster who achieved multiple 1st place finishes in global Kaggle competitions, and top global rank at 12th of 50,000+
Content Consultant for Applied Data Science with Venture Applications: Data-X (INDENG 135/235) at University of California, Berkeley
Site: forecastegy.com
Follow me on Twitter: mariofilhoml
Kaggle profile: www.kaggle.com/mariofilho
LinkedIn: linkedin.com/in/mariofilho/
🤖 Building machine learning systems since 2014
🏆 2x Prize Winner Kaggle Competitions Grandmaster
📊 Former Lead Data Scientist @ Upwork
🎓 @UCBerkeley Data-X Consultant
Fix Imbalanced Data In Machine Learning
A simple trick to deal with imbalanced classes when training machine learning models with code examples in Scikit-learn, XGBoost, and Tensorflow/Keras.
Remember to like and subscribe. Thanks!
*Video style heavily inspired by @Fireship
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
// SUPPORT THE CHANNEL 👇❤️
Sign up for a Coursera course:
imp.i384100.net/EaDmQe
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
// SOCIAL MEDIA
LinkedIn: www.linkedin.com/in/mariofilho/
Kaggle: kaggle.com/mariofilho
Twitter: mariofilhoml
Blog: forecastegy.com
Some links above can be from partnerships where I get a commission if you buy a product, without any additional cost to you. Thanks for the support!
Remember to like and subscribe. Thanks!
*Video style heavily inspired by @Fireship
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
// SUPPORT THE CHANNEL 👇❤️
Sign up for a Coursera course:
imp.i384100.net/EaDmQe
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
// SOCIAL MEDIA
LinkedIn: www.linkedin.com/in/mariofilho/
Kaggle: kaggle.com/mariofilho
Twitter: mariofilhoml
Blog: forecastegy.com
Some links above can be from partnerships where I get a commission if you buy a product, without any additional cost to you. Thanks for the support!
มุมมอง: 1 508
วีดีโอ
Feature Engineering Secret From A Kaggle Grandmaster
มุมมอง 40K3 ปีที่แล้ว
Learn how to do feature engineering for tabular data like a Kaggle Grandmaster and get high-performance machine learning models. Like the video? Subscribe and turn on the notifications to get more tips :) 0:00 Intro 1:38 The One Question To Ask Yourself 2:40 Credit Card Fraud Examples 6:34 Brief Info On Categorical Features 7:23 Time Series Feature Engineering 11:53 An Extremely Valuable Exerci...
How To Fill Missing Data With Pandas Fillna - Data Science For Beginners
มุมมอง 8253 ปีที่แล้ว
Check my blog for more machine learning content: forecastegy.com Learn how to replace missing values in your pandas DataFrame with the fillna function. Like the video? Subscribe and turn on the notifications to get more tips :) Docs: pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.fillna.html
How To Drop Columns In a Pandas DataFrame - Data Science For Beginners
มุมมอง 4473 ปีที่แล้ว
Check my blog for more machine learning content: forecastegy.com Learn how to drop one or more columns in a DataFrame using pandas. Like the video? Subscribe and turn on the notifications to get more tips :) Docs: pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop.html
Multiple Time Series Forecasting With Scikit-Learn
มุมมอง 37K3 ปีที่แล้ว
You got a lot of time series data points and want to predict the next step (or steps). What should you do now? Train a model for each series? Is there a way to fit a model for all the series together? Which is better? I have seen many data scientists think about approaching this problem by creating a single model for each product. Although this is one of the possible solutions, it's not likely ...