Project 10. Credit Card Fraud Detection using Machine Learning in Python | Machine Learning Projects

. In this video we have built a Credit card Fraud Detection system using Machine Learning with Python. For this project, we have used the Logistic Regression model.

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Hi guys! I am Siddhardhan. I work in the field of Data Science and Machine Learning. It all started with my curiosity to learn about Artificial Intelligence and the ability of AI to solve several Real Life Problems. I worked on several Machine Learning & Deep Learning projects involving Computer Vision.
I am on this journey to empower as many students & working professionals as possible with the knowledge of Machine Learning and Artificial Intelligence.

I am making a "Hands-on Machine Learning Course with Python" in YouTube. I'll be posting 3 videos per week: Monday Evening; Wednesday Evening; Friday Evening.

[marcoandresc.]

Many YouTube videos and even courses in Spanish do not explain very well and do not cover everything necessary to do a machine learning project, but you explain it very well. I'm not very good at English but I understood the procedure very well, excellent video

[yassine.h]

Great.
I would like to add some remarks that might help in future projects :
- The way you dealed with imbalanced data will certainly lead to bad predictions, because alot of information were lost when taking a small sample from a large dataset.
- use SMOTE instead of sampling
- use decision trees or random forests algos they are better when dealing with imbalanced data
- use more evaluation metrics like ROC curve, F1 score, recall...

[rajatagarwal]

wow, this is such a fluent, smooth explainer, I am a mere beginner, and still able to understand almost everything. My teacher was not even able to explain a line of it correctly.

[sailakshmi]

I just want to suggest few points before you post a project
1. Goal of the Project
2. Output of this
3. ways that it can be implemented
4. in realworld how it is checked with the user inputs

I think this basic points must be mentioned in the project to be called it as a meaning full project.
Anyways thanks for your contribution @Siddhardhan

[kamaleshsenthilmurugan]

Extraordinary content! I have watched all your videos from hands on ml course to this one.Everything was explained such that even a beginner would understand it. You have a really great gift in teaching complex stuff in a easy manner. My request to you is to keep teaching like this so that you will be able to change the life of lots of people like me. I am going to recommend this channel to all my juniors and friends.

[subhamsaha]

Very nice explanation and really liked the video. The classification report is also very good measure of the model. I think if we do cross validation and use some boosting techniques then the score can be increased more and one more imp thing is that here accuracy score doesnt matters, main is precision and recall because we cant let a fraud trans to become non fraud. Thank you

[west]

Hi, Siddhardhan
"I just wanted to take a moment to express my sincere gratitude for the excellent tutorial on Credit Card Fraud Detection using Machine Learning in Python that you posted on YouTube. Your clear and concise explanations, combined with the practical examples, have helped me tremendously in understanding the fundamentals of this complex topic. Your dedication to providing high-quality content is evident, and I appreciate the time and effort you put into creating such an informative tutorial. Once again, thank you so much for sharing your knowledge with the world - you're making a positive impact on the lives of many, including mine."

[virago]

The way you explained was really amazing. I was able to clear all my doubts regarding this project. Keep up the good work and seriously thanks a lot for providing such a great content!!!!

[sandipansarkar]

finished coding practice .Feeling a lot confident

[rohitsarkar]

A great teacher ❤️❤️❤️❤️❤️❤️ i have ever seen in my life...who is explaining each and every line of a big project code🔥🔥🔥🔥🔥🔥🔥🔥

[jeeruveeresh]

simple and nice explanation..., I didn't no machine learning. just, I know python but the way of your explanation helps me lot to understand machine learning.Thanks a lot.

[divyanshsingh]

bro->
Accuracy of training data=98.61%
Accuracy of testing data=84.375%

[saisasikanthduvvuri]

Hello, @Siddhardhan Your presentation feed me more than I thought. Really awesome accuracy score and good EDA. Thank you for your video.

[adityams]

**Bro you dont use Accuracy as a metric here, you can get 99% without doing all the preprocessing you just did. Use F1 or TPR or FPR or AUC ROC!**

[mamondhar]

Really explain step by step very easy way . Want more vdo on machine learning as Covid Detection etc

[JayashreeS-nnrk]

hi siddhardhan,
I have an error, kindly resolve it.# training the Logistic Regression Model with Training Data
model.fit(X_train, Y_train)...in this part, I got STOP:TOTAL NO OF ITERATIONS REACHED LIMIT.How can i resolve it,

[adnanemehdaoui]

we can use smote method to resolve unbalanced data, it very useful also

[tahiraleem]

Thanks a lot Sid sir. Love and support from Pakistan.

[kandrunaresh-mxzj]

Hi siddhardhan..Your explaination is awesome.. keep up the good work..Nice comparision between over fitting and under fitting over accuracy.. and nice example too..

[niteshprajapat]

Thank You Sir, It was one of the best tutorials ever and I loved the way you explaining all lillte things in easiest way..