and not just ask, but know when the results/answer actually make sense as I've gotten incorrect answers from chat gpt before when I asked it to perform some stats for me.
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.
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 😅
It will not work at maximum , 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)
@@hayksergoyan8914 commenting about this AI 1 year later is equal to answering your mom shouting from the kitchen by the time you become a grandpa 💀 (jk)
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)
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
Ciao, sono Alessandro un personal Trainer e vorrei che tu mi aiutassi a sviluppare un GPTs che riesca a programmare in modo ottimale gli allenamenti in modo personalizzato per i miei clienti, basandosi solo sul mio materiale di studio. Fornendo le giuste progressioni, voglio che in base a quello che gli dico (anamnesi del soggetto) lui riesca a sviluppare un ottimo programma come faccio io così da aiutarmi ad essere più efficiente nel mio lavoro.
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?!
Hi Kunal, AI is definitely going to have an impact on the way we work, for all industries. But I like the example of accountants, who theoretically could have been replaced by software automation many years ago. However, we still need accountants for their expert judgement and specific knowledge to solve problems. I think the same will happen to Data Analytics/Science. It will be a tool for us to work faster and take on more projects.
As a data scientist There are way too many errors in approach here, when you work on real world data rather than showing a tutorial on curated data 1. No EDA, you just dove right in to a model Initial eda is crucial to understand what is wrong with the data and how it behaves 2. Leaky Fit-transform of dummy variables, and very little preprocessing overall 3. Tuning the best un-tuned model is not necessarily the best model overall Many models can be very bad untuned and drastically better when properly tuned Chat gpt is a powerful tool that can drastically improve the workflow of any industry But, as shown here, you always need to ask the right questions and keep checking your flow in order to get the best results
hi dave. please share the tutorial about using python with visual studio code like this video, plus python environment setting and interface result. I wanna create machine learning codes using VSC too🙏🏻🙏🏻 thanks
my python sucks balls; however I do have a masters degree in data sci (good grade too); do people think its cheating or will look stupid I I start issuing chat gpt to do most of my code at work; and people can see? I mean I know the theory and what to ask and edit code when required??? thoughts!!
Not at all! Use the tool to help you out and learn. As you work with it, you'll get a better understanding of Python. You can just ask it to explain the code as well. In my opinion, the best way to learn python for data science right now is to do projects slightly out of your comfort zone with the help of ChatGPT and GitHub Copilot.
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.
Thanks Ivan, and exactly! Exciting times ahead.
I couldn’t agree more!!
and not just ask, but know when the results/answer actually make sense as I've gotten incorrect answers from chat gpt before when I asked it to perform some stats for me.
You've said it right! Knowing how to ask right questions to AI is going to be the most in-demand skill.
Using Jupyter notebook will make ChatGPT explanations easy to teach yourself. Its cool if you try doing it again by yourself after copy-pasting.
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.
Man I resonated so much with the excitement, I was looking EXACLY for THIS video
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 😅
Haha yea same, It's so good right!
From "Data Science" to "Question Science"
It will not work at maximum , 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)
@@hayksergoyan8914 commenting about this AI 1 year later is equal to answering your mom shouting from the kitchen by the time you become a grandpa 💀 (jk)
@@axel_r_ funny)) But I am using chat gpt since it was produced for public, just passing over this video wrote a comment)
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)
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
Hi. Can you please build one as a roulette Predictor?
Yo just months ago this would’ve been a 2 hr tutorial broken up into a playlist
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.
Please make episode about ci/cd in data science
Great video
It make your work more efficient!!
which chatgpt is this?
Why would I create machine learnin model ?
Ciao, sono Alessandro un personal Trainer e vorrei che tu mi aiutassi a sviluppare un GPTs che riesca a programmare in modo ottimale gli allenamenti in modo personalizzato per i miei clienti, basandosi solo sul mio materiale di studio. Fornendo le giuste progressioni, voglio che in base a quello che gli dico (anamnesi del soggetto) lui riesca a sviluppare un ottimo programma come faccio io così da aiutarmi ad essere più efficiente nel mio lavoro.
I very much enjoyed the video, thank you for sharing!
Nice work!! Is there a chance to download your final script as well ?
Great work, very informative video.
Thanks Ali!
Great video, you are just what I was looking for
Glad I can help!
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?!
Hi Dave,
Wouldn't it be possible for the client himself to do things with ChatGPT if things became too simple?
Hi Kunal, AI is definitely going to have an impact on the way we work, for all industries. But I like the example of accountants, who theoretically could have been replaced by software automation many years ago. However, we still need accountants for their expert judgement and specific knowledge to solve problems. I think the same will happen to Data Analytics/Science. It will be a tool for us to work faster and take on more projects.
Can you make a video on how to to deploy the model and make predictions. Thank you great video.
Hi Tony, yes I am going to make videos about that ;)
Great tutorial - would just do all of this out of colab imo
Thanks for sharing 🙏
Such a great example !
Thanks!
this is just great!!! Thanks!!!
You're welcome! 🙌🏻
Great vid as always 🙌, definitely been using gpt a lot at work
Thanks Nash, don't tell the managers haha 🤫
Awesome. Thank you 👋👋👋👋👋
You're welcome!
As a data scientist
There are way too many errors in approach here, when you work on real world data rather than showing a tutorial on curated data
1. No EDA, you just dove right in to a model
Initial eda is crucial to understand what is wrong with the data and how it behaves
2. Leaky Fit-transform of dummy variables, and very little preprocessing overall
3. Tuning the best un-tuned model is not necessarily the best model overall
Many models can be very bad untuned and drastically better when properly tuned
Chat gpt is a powerful tool that can drastically improve the workflow of any industry
But, as shown here, you always need to ask the right questions and keep checking your flow in order to get the best results
Great !!
hi dave. please share the tutorial about using python with visual studio code like this video, plus python environment setting and interface result. I wanna create machine learning codes using VSC too🙏🏻🙏🏻 thanks
Hi Lani, you can check out the tutorial here: th-cam.com/video/zulGMYg0v6U/w-d-xo.html
@@daveebbelaar awesome. thank youuu Dave! 🚴♂️
goeie video man
Thanks!! 🙏🏻
my python sucks balls; however I do have a masters degree in data sci (good grade too); do people think its cheating or will look stupid I I start issuing chat gpt to do most of my code at work; and people can see? I mean I know the theory and what to ask and edit code when required??? thoughts!!
Not at all! Use the tool to help you out and learn. As you work with it, you'll get a better understanding of Python. You can just ask it to explain the code as well. In my opinion, the best way to learn python for data science right now is to do projects slightly out of your comfort zone with the help of ChatGPT and GitHub Copilot.
thank you
Great