Data Science Project- Credit Card Fraud Detection using Machine Learning | Python Training |Edureka

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This Edureka Live on Data Science Project-3 will help you understand how we can use the logistic regression algorithm to predict outcomes based on data-driven insights.

#PythonEdureka #Edureka #datascienceproject #pythonprojects #pythonprogramming #pythontutorial #PythonTraining

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How it Works?
1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

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About the course

Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing.

Edureka's Python Certification Training not only focuses on the fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands-on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problems that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross-Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds.

Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms.

Edureka’s Python course will also cover both basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. You will use libraries like pandas, numpy, matplotlib, scikit, and master concepts like Python machine learning, scripts, and sequence.

Why learn Python?

It's continued to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built-in debugger.

It runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for commercial products, because of its OSI-approved open source license.

It has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that it is the " Next Big Thing " and a must for Professionals in the Data Analytics domain.

Who Should Go For This Course?

Programmers, Developers, Technical Leads, Architects
Developers aspiring to be a ‘Machine Learning Engineer'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'Python' professionals who want to design automatic predictive models

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I can't believe how logistic model gets too much accuracy even without balancing the dataset.🧐

anmolkumarchauhan
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I can't believe someone ran a Log classifier on such imbalanced data and provided "Accuracy" as a metric and said it's a good classifier of 99% accuracy. Never trust accuracy as a metric when doing classification. Guys: Look at your precision, recall for a better metric. Perform sampling techniques, even if it's SMOTE. See how good your AUC and ROC is.

mohammedismailkhan
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Hi, can you do one project of Gene Expression Data (specially of Cancer Prediction ). It will help me a lot in my project.
@edureka! team

afsahkhurshid
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Good video sir, Very helpful.
Sir, can we expect some R programming project videos too like related to data science only.

ShreyA-mspe
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Can you please share data set, so we can practice, what we learned

ims
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Ok. good work. now plz make a video on the disease detection from patients and also mention that which algorithm will use to detect the diseases in human body??? wait U soon plz

clickmintaka
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when you create these videos provide links to datasets we need to follow along

TheInfluenceMandate
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Team i request u to provide the atleast similar dataset, so we can practice

shubhamgove
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Why r u checking the Accuracy when u r working in an imbalanced dataset and u r working with minority data?? and why didnt u normalise or upsample/downsample??

samratsengupta
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This dataset is highly unbalanced ...we can't simply fit it in our model...?if we predict all the transactions are legitimate then also we'll get accuracy more than 98...which is simply not correct.

bikrantanand
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What do the columns v1-v28 denote in the dataset? Also, what are these negative values related to these transaction details?

midevkm
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Pls make a video on how to make a festival wishing websites

sandy-sjir
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I think a better metric would be precision for imbalanced dataset.

manhalrahman
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is there a project for visual recognition ??

omankhan
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Pls do on forest fire detection pls pls

dayasagar
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Can you plz mention the dataset used in the videos link

anusuyadevi
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I am not getting the output after this command - sns.relplot(x="Amount", y="Time", hue="Class", data=data). What to do?

shivanigupta
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Hi I'm unable to load the dataset from its path. could you please tell me how to load a dataset

SaadMamindla
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when i write down this code error shown because of keyword class.sir what is the solution???

susmitaghanta
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Mine is bringing up errors saying,

ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
Please also refer to the documentation for alternative solver options:
extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG,

taku
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