Ever since I came across your videos, I can't stop watching. I've seen a lot on the internet, but you are the only ones who can present information so clearly. Thank U a lot!
00:04 Training a machine learning model using scikit-learn 02:15 Scikit-learn provides useful metrics and pre-prepared datasets for machine learning. 04:29 Splitting Data into Train, Test, and Validation Sets 06:49 The main steps in the process are data set sampling, model training, and model selection 08:59 Scikit-learn documentation provides thorough explanations and examples of importing and using different algorithms and models. 11:10 There are multiple ways to evaluate machine learning models 13:25 Creating a confusion matrix and classification report using Seaborn and scikit-learn 15:42 Accuracy alone may not provide a complete picture of model performance. 17:46 GridSearchCV helps create and compare multiple models with different hyperparameters. 19:41 Grid search includes cross-validation for training models with different parameter combinations. 21:44 Get started with scikit-learn: data preparation, model training, and evaluation. Crafted by Merlin AI.
Not a big deal since you didn't change any default parameters but you implemented a classifier while showing the regression documentation Great high level overview of the ML training process.
We got the setup, prepared the data, we did the training and the validation. But in the end we never got to use the model. I thought this would be the most important part.
Not a step by step guide this time, I was able to follow along though the code errors just after In [44] as X_resampled is not defined. Interestingly my seaborn heatmap was mostly dark.
Thanks for the explanation mam it helped , i m having a doubt with my project....see as i working on a AI LLM module so I have completed the training the dataset and all that stuff....now i stucked at testing the module I m not getting that how to test your module..... Can you please guide over that....like maybe a proper video describing how to test you ML Models r AI LLM modules.....it will help a lot mam!!....I need it!!.....❤
Well explained however I feel it was a little bit rushed. I'm wondering why the model (shown in the classification_report) is still so unbalanced even after RandomOversamlper did rebalance the classes. Anyway PCA and dimensionality reduction topics are welcomed even to complement this tutorial, given you've skip to encode the other non numerical data that could have provided good insight for the model and provide better AP
Hi @Misra, I'm using the flights dataset, full as submited in Kaggle, I'm running the clf = RandomForestClassifier(random_state=0) followed by the cross_val_score and it stay for so long time processing and don't finish at least with 1:30 hour. I'm using a MacBook Pro M1 with 64GB , Is there anything that I'm missing?
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Ever since I came across your videos, I can't stop watching. I've seen a lot on the internet, but you are the only ones who can present information so clearly. Thank U a lot!
True, absolutely clear
Great course. Just a thought, would be nice to add a #4 where you pick one and go through it together with us and slowly. Again, very well done!
00:04 Training a machine learning model using scikit-learn
02:15 Scikit-learn provides useful metrics and pre-prepared datasets for machine learning.
04:29 Splitting Data into Train, Test, and Validation Sets
06:49 The main steps in the process are data set sampling, model training, and model selection
08:59 Scikit-learn documentation provides thorough explanations and examples of importing and using different algorithms and models.
11:10 There are multiple ways to evaluate machine learning models
13:25 Creating a confusion matrix and classification report using Seaborn and scikit-learn
15:42 Accuracy alone may not provide a complete picture of model performance.
17:46 GridSearchCV helps create and compare multiple models with different hyperparameters.
19:41 Grid search includes cross-validation for training models with different parameter combinations.
21:44 Get started with scikit-learn: data preparation, model training, and evaluation.
Crafted by Merlin AI.
Not a big deal since you didn't change any default parameters but you implemented a classifier while showing the regression documentation
Great high level overview of the ML training process.
Thank you!
We got the setup, prepared the data, we did the training and the validation. But in the end we never got to use the model. I thought this would be the most important part.
So well explained. Thank you!
You're very welcome!
Not a step by step guide this time, I was able to follow along though the code errors just after In [44] as X_resampled is not defined. Interestingly my seaborn heatmap was mostly dark.
greattt ilu!
This is great, thank you!
Where can I get the cheat sheet for choosing model
Thanks for the explanation mam it helped , i m having a doubt with my project....see as i working on a AI LLM module so I have completed the training the dataset and all that stuff....now i stucked at testing the module I m not getting that how to test your module.....
Can you please guide over that....like maybe a proper video describing how to test you ML Models r AI LLM modules.....it will help a lot mam!!....I need it!!.....❤
Well explained however I feel it was a little bit rushed.
I'm wondering why the model (shown in the classification_report) is still so unbalanced even after RandomOversamlper did rebalance the classes.
Anyway PCA and dimensionality reduction topics are welcomed even to complement this tutorial, given you've skip to encode the other non numerical data that could have provided good insight for the model and provide better AP
Great video! And she is the most beautiful programmer I have ever seen ❤
Hi @Misra,
I'm using the flights dataset, full as submited in Kaggle, I'm running the clf = RandomForestClassifier(random_state=0) followed by the cross_val_score and it stay for so long time processing and don't finish at least with 1:30 hour. I'm using a MacBook Pro M1 with 64GB , Is there anything that I'm missing?
Great Video!!!
Thank you!
Playlist please
th-cam.com/play/PLcWfeUsAys2lpJzESyeRUVvJlU6ycjr-b.html
why not simply show examples step by step, rather than explaining stuff we dont even do?
PS: the git does not match what you show here
Hyten:-)
Yo
😂😂😂. Dam Decease some easy two watch