Automate Machine Learning with ChatGPT

Learn how you can save hours of time on your machine learning and data science projects.

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[i.zhirnov]

I believe this is a perfect example of the ChatGPT complementing the work of a Data Scientist, you need to know what to ask, right. Thank you, Dave.

[shaktisingh]

You've said it right! Knowing how to ask right questions to AI is going to be the most in-demand skill.

[ofelipe.amorim]

Man I resonated so much with the excitement, I was looking EXACLY for THIS video

[TruthEagle]

Using Jupyter notebook will make ChatGPT explanations easy to teach yourself. Its cool if you try doing it again by yourself after copy-pasting.

[israelazoulay]

Nice job and great video bro! Continue like this, appreciate it! However, I think there is an error in your code which significantly affects your model performance and accuracy making it of 85%, since you are supposed to split your dataset into training and testing sets before applying any transformations including the 'get_dummies()' method for handling categorical variables, because otherwise you cause a data leakage - where information from the test set inadvertently influences the training process, leading to overly optimistic performance estimates.
And indeed, if you will restructure the process of your code and make the changes I described above, you will probably notice a significant lower accuracy of your model, reflecting real world cases.

[axel_r_]

This has changed the game entirely.
From now on, schools should teach students how to use this AI and how to maximise desired outcomes of any known and unknown achievements.
I will never be able to program anything without this AI again 😅

[jimmytorres]

Can you make a video about how to be a freelance data scientis? How did you get started? Recommendations, how to get clients and how to actually concrete a business and general stuff like that. It'd be amazing

[hayksergoyan]

It will not work at maximum for all users, because for asking some specific questions about project and knowing some coding, and network architecture nuances will help you tondo that work much better and faster than for some person who doesn't know math or some coding. This will only save tour time and give more data to openai for boosting their own projects)

[tomkmb]

bit weird, I was following along with this tutorial and when evaluating the best model to go with I got these results -

Model: Ridge Regression
Mean Squared Error: 51.64
R-squared: 0.80

Model: Random Forest
Mean Squared Error: 54.34
R-squared: 0.79

Model: Gradient Boosting
Mean Squared Error: 51.61
R-squared: 0.80

Model: Support Vector Machine
Mean Squared Error: 59.99
R-squared: 0.77

Model: K-Nearest Neighbors
Mean Squared Error: 68.27
R-squared: 0.74


Gradient Boosting is the slight favourite, next I followed along with the tuning Hyperparameters with a grid search etc exactly as written in the video and I ended up getting a worse accuracy?

Best Model:
GradientBoostingRegressor(learning_rate=0.01, n_estimators=50, random_state=42)
Best Mean Squared Error: 148.50
Best R-squared: 0.38

What's happened there?!

[MeshRoun]

I very much enjoyed the video, thank you for sharing!

[youssefadel]

Please make episode about ci/cd in data science

[Koraball]

Hi. Can you please build one as a roulette Predictor?

[TheAnonJohn]

Great video, you are just what I was looking for

[buqrepb]

Yo just months ago this would’ve been a 2 hr tutorial broken up into a playlist

[seyhava]

It is a great video but can I get the link to see your prompt on chatgpt since when you prompt, it so fast and I can't see all of your prompt.

[tonypham]

Can you make a video on how to to deploy the model and make predictions. Thank you great video.

[LichtMoo]

Nice work!! Is there a chance to download your final script as well ?

[MyBrianBailey]

Great tutorial - would just do all of this out of colab imo

[haarTrick]

Why would I create machine learnin model ?

[kunalkumbhar]

Hi Dave,
Wouldn't it be possible for the client himself to do things with ChatGPT if things became too simple?