Understanding Bias and Variance in Machine Learning
Bias refers to the error in the model when the model is not able to capture the pattern in the data and what results is an underfit model (High Bias).
Variance refers to the error in the model, when the model is too much tailored to the training data and fails to generalise for unseen data which refers to an overfit model (High Variance)
There should be a tradeoff between bias and variance. An optimal model should have Low Bias and Low Variance so as to avoid underfitting and overfitting.
Techniques like cross validation can be helpful in these cases.
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Bias refers to the error in the model when the model is not able to capture the pattern in the data and what results is an underfit model (High Bias).
Variance refers to the error in the model, when the model is too much tailored to the training data and fails to generalise for unseen data which refers to an overfit model (High Variance)
There should be a tradeoff between bias and variance. An optimal model should have Low Bias and Low Variance so as to avoid underfitting and overfitting.
Techniques like cross validation can be helpful in these cases.
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AutoML_Alex
State-of-the art Automated Machine Learning python library for Tabular Data
Creator: Alex Lekov
Stars ⭐️: 191
Forked By: 41
https://github.com/Alex-Lekov/AutoML_Alex
#ml #machinelarning #datascience
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State-of-the art Automated Machine Learning python library for Tabular Data
Creator: Alex Lekov
Stars ⭐️: 191
Forked By: 41
https://github.com/Alex-Lekov/AutoML_Alex
#ml #machinelarning #datascience
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GitHub
GitHub - Alex-Lekov/AutoML_Alex: State-of-the art Automated Machine Learning python library for Tabular Data
State-of-the art Automated Machine Learning python library for Tabular Data - Alex-Lekov/AutoML_Alex
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Roadmap to Learn Data Science
The Art Of Data Science.pdf
6.2 MB
The Art Of Data Science
Vital Cheatsheets (1).pdf
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Vital Cheat sheets for Data Scientists and Machine Learning Engineers
🏆 Top results in the quiz 'Data Science Quiz'
One new name among winners
Core X emerged as this round champion 🍾
🤓 251 people took the quiz
🥇 Core X – 8 (15 sec)
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19. Python Programmer – 8 (2 min 5 sec)
20. @EvertonCSantana – 8 (2 min 13 sec)
Next (and last) round:
C/C++/OOP Quiz
End date: March 3nd (Sunday)
One new name among winners
Core X emerged as this round champion 🍾
🤓 251 people took the quiz
🥇 Core X – 8 (15 sec)
🥈 Jagan Reddy – 8 (19.4 sec)
🥉 @DarkAngeI7887 – 8 (30 sec)
4. @mutaician0 – 8 (38.3 sec)
5. @Olamilekan_ayinde – 8 (41.6 sec)
6. @Eraullux – 8 (45.3 sec)
7. @Kdrakex – 8 (46.1 sec)
8. X M – 8 (49 sec)
9. Neha K – 8 (51.5 sec)
10. @santhu15 – 8 (53.9 sec)
11. @mk_12077 – 8 (56 sec)
12. @CosmicDust1 – 8 (1 min 1 sec)
13. mr unknown – 8 (1 min 6 sec)
14. Helario H – 8 (1 min 14 sec)
15. @FutureMillionaire03 – 8 (1 min 14 sec)
16. @Adilkhatik – 8 (1 min 30 sec)
17. @ycx1205 – 8 (1 min 30 sec)
18. @puneetc30 – 8 (1 min 33 sec)
19. Python Programmer – 8 (2 min 5 sec)
20. @EvertonCSantana – 8 (2 min 13 sec)
Next (and last) round:
C/C++/OOP Quiz
End date: March 3nd (Sunday)
Explore Population Pyramids with Python and Web Applications
Let's Understand Past, Present and Future Population Growth Using Python and Port our Findings to the Web for the World!
Rating ⭐️: 4.6 out 5
Students 👨🎓 : 9652
Duration ⏰ : 1hr 4min on-demand video
Created by 👨🏫: Manuel Amunategui
🔗 Course Link
#Data_Science #python
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Let's Understand Past, Present and Future Population Growth Using Python and Port our Findings to the Web for the World!
Rating ⭐️: 4.6 out 5
Students 👨🎓 : 9652
Duration ⏰ : 1hr 4min on-demand video
Created by 👨🏫: Manuel Amunategui
🔗 Course Link
#Data_Science #python
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Udemy
Free Data Science Tutorial - Explore Population Pyramids with Python and Web Applications
Let's Understand Past, Present and Future Population Growth Using Python and Port our Findings to the Web for the World! - Free Course
🔥WEBSITES TO GET FREE DATA SCIENCE CERTIFICATIONS🔥
👌. Kaggle: http://kaggle.com
👌. freeCodeCamp: http://freecodecamp.org
👌. Cognitive Class: http://cognitiveclass.ai
👌. Microsoft Learn: http://learn.microsoft.com
👌. Google's Learning Platform: https://developers.google.com/learn
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👌. Kaggle: http://kaggle.com
👌. freeCodeCamp: http://freecodecamp.org
👌. Cognitive Class: http://cognitiveclass.ai
👌. Microsoft Learn: http://learn.microsoft.com
👌. Google's Learning Platform: https://developers.google.com/learn
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Kaggle
Kaggle: Your Machine Learning and Data Science Community
Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals.
Dear Community,
It's become challenging to balance content creation alongside my full-time job and creation of app that will give you any course for free - I am working on that after work for previous 8 months).
This is why I've assembled a team (15 people atm) to help. They're compensated from my own pocket, so I decided to occasionally post some ads to at least reduce the costs of maintaining our community a little bit.
Rest assured, any ads will be clearly labeled, and I'll give my best to filter out any scams.
Thank you for your support and understanding!
For any questions feel free to contact me directly at @mldatascientist
Warm regards,
Big Data specialist
It's become challenging to balance content creation alongside my full-time job and creation of app that will give you any course for free - I am working on that after work for previous 8 months).
This is why I've assembled a team (15 people atm) to help. They're compensated from my own pocket, so I decided to occasionally post some ads to at least reduce the costs of maintaining our community a little bit.
Rest assured, any ads will be clearly labeled, and I'll give my best to filter out any scams.
Thank you for your support and understanding!
For any questions feel free to contact me directly at @mldatascientist
Warm regards,
Big Data specialist