I have been swamped in my machine learning and deep learning journey. I thought I would share a quick update from my latest Kaggle escapadeโI've reached 99% accuracy on the classic Dogs vs. Cats image classification challenge using transfer learning. It's been an incredible journey tweaking and training the models to spot our furry friends with near-perfect precision. Eager to see what's next on the horizon! ๐ถ๐ฑ๐ฏ #Kaggle #DogsVsCats #DeepLearningWin
My first entry into a @Kaggle competition and I'm in the top 5%! ๐ฅณ
I built Machine learning and Deep Learning models to predict bank customer churn using a dataset from @Kaggle.
The model uses:
1. Machine Learning models - Ensemble and Boosting.
2. Deep Learning - Sequential Model Creation.
It achieved a score of 88.632% on the test set! ๐
While I didn't win, I'm proud of cracking the top 5%. Thanks to @Kaggle for the data and platform to learn #MachineLearning.
Sharing my code here for anyone starting their #Kaggle journey: https://t.co/NVESCKfgkf
Let me know if you have any other tips to improve! Next stop - a #Kaggle competition win haha!
Please upvote and comment!! ๐
Hello everyone,
Just a couple of months into my #MachineLearning & #DeepLearning journey, I'm thrilled with the progress! From grappling with models to training them to make predictions, it's been a wild ride. ๐ข And guess what? My first dataset tackled heart disease prediction with solid accuracy! ๐ Facing my fear of machine learning head-on has truly paid off. Can't wait to dive deeper. Join me on this inspiring adventure? I'd love to hear your thoughts and tips for the journey ahead!
Check out my Kaggle notebook here:
https://t.co/Tiaqy4pzFm
#DataScience