Step by Step Tutorial on Logistic Regression in Python | sklearn |Jupyter Notebook
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- Опубликовано: 17 май 2022
- This video tries to give you a basic understanding of logistic regression and works on a logistic regression problem from beginning to end using a real dataset. Please excuse my sound quality. I will try to improve it in the future.
Here is the link to the dataset used in this video:
github.com/rashida048/Dataset...
Please feel free to check out my Data Science blog where you will find a lot of data visualization, exploratory data analysis, statistical analysis, machine learning, natural language processing, and computer vision tutorials and projects:
regenerativetoday.com/
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/ rashida048
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#logisticRegression #machinelearning #datascience #dataAnalytics #python #sklearn #jupyternotebook
Thank you so much for this!!!!! You have no idea how much it helps :D
Thank you SO MUCH for this. You're an amazing teacher, and this class was definitely really helpful!
Thank you so much for your time and effort !!! I am waiting for your next videos about other argorithms for the classification problems !!
Thank you so much for this amazing explanation. You're the best at explaining logistic regression! You deserve way more recognition!
all clear, to the point video with 0 nonsense. thanks a lot
Such an underrated channel for how accurate and straight to point is the content compared to other channels with lots of unnecessary talks....you earned a subscriber!, I'm definitely recommending your channel if anyone enquired about your content
Honestly!!!!🤧🤧
Big kudos to your teachings
Thanks a lot for your explanation, it gives me a new sight for this topic
Took me about an hour but this was my first introduction to Python. thanks!
Very well explained I was struggling with many things and your accurate explaination cleared many doubts. Thankyou and please countinue uploading. This was Veeeery helpful !
Thank you! this is excellent
Thanks for your sharing, I currently get trapped in how to conduct logistic regression model in Python, you just save me, thanks a lot again!
Well Explained the complicated Algorithms....Thank You.
Request for more Machine Learning Videos in details.
at last something hands on with real problems. I'm tired of maths abstract bullshit formulas....
Thanks a lot !!!
Perfect
awesome implementation of logistic regression. Another way to measure the accuracy is to use confusion matrix and accuracy score metrics
Thanks a lot
🤩🤩
Hi your voice sooooo calm and cool
Upload more video
by using log_reg.score() for each (x,train ,and x_ test) it replace the other sq errors right?
Thaaaaaaaaanks
I just love you so much right now
So how to know which of the independent variables strongly impacts the dependent variable?
Do correlation with variables through Berson(r)
As I am teaching myself about Logistic Regression with SKLearn, I read in the documentation that fit_intercept defaults to True, so it would have been running in all your calculations.I'm wondering why it was added as True?
simple and very easy to understand ....loved it!!!
do you have an instagram channel?
Can you explain why random state=0
aren't we supposed to use "family = sm.families.Binomial()" when building the logistic regression model in "sm.GLM(y_train, X_train, family = sm.families.Binomial())"
Please explain.
can you make a video and explain how to visualize logistic regression?
when we use cat.cosd and one hot encoder ?
why u didnt use one hot encoder ? please im confused with this
Your video is so much helpful... But there is voice problem..sometimes its became high
Yes, I noticed it. I just couldn't find time to redo it. So uploaded it as it is. Thanks for watching! and Sorry about that experience!
I have a question.
1) .score that represent R-square in Logistic Regression model. Why it can interpret accuracy of the regression?
2) I use confusion matrix to find accuracy. is it a same solution or not and why?
In classification you can get exact same class. So accuracy can be a metric and you can canculate confusion matrix. But in regression exact match doesn't happen usually. If you try to find accuracy you will get 0% accuracy most of the time. The prediction is mostly an estimation. So you evaluate the model by using R-squared or mean absolute error or mean squared error, or something similar.
@@regenerativetoday4244 Thank you so much!!!! I appreciate it