Online Summer Training in Machine Learning and Data Science with Python | Class-10

Agenda of Session-
What is Classification?
Classification vs Regression
What is Regression?
Logistic Regression in Python
Logistic Regression vs Linear Regression
Logistic regression and iris flowers classification problem!
Confusion Matrix and Accuracy

Reference Notes -

Attendance Rules:

1. Write Session Summery below the YouTube Video after Every Class.

2. Solve assignment after Every Class on:

3. Solve Given Task and Share to your Linkedin Profile after every class.

Do attendance formalities with your Registration IDs.

****** Attendance Rules are Compulsory for Summer Training Certification.
#LinearRegression #MachineLearning #PythonOnlineTraining #PythonTraining #datasciencetraining

[srishtikohli]

in today's session we learnt about linear regression and logistic regression classification and difference between two, matrix.

[GAURAVKUMAR-bcvd]

GO_STP_1075
Today we learnt about Logistic regression, implemented on iris dataset and learnt about evaluation metricses like confusion matrix, Precision, recall.

[nikitajain]

In this session we learnt about classification and difference between classification and regression, confusion matrix, accuracy and precision.

[raviz]

In this session we learnt about logistic regression and implemented it to solve a classification problem. We also learnt about evaluating the model using confusion matrix and accuracy.

[vishalsonawane]

GO_STP_193
we learned about Logistic regression, Confusion Matrix, Accuracy, Sensitivity and Recall with Iris Dataset

[sakshichavan]

GO_STP_440
Day 10:
In todays session, I learned about the logistic regression and the classification of logistic regression. Also learnt about scaling of data, confusion matirx, accuracy, precision, recall and understood the logistic regression using the iris dataset .

[priyadarshanisingh]

In this session, we learnt about classification and looked into the different between linear and logistic regression. We learnt the types of logistic regression : binary, multinomial, ordinal. We used the Iris data set and implemented logistic regression. We learnt different methods for evaluating predictions, confusion matrix, accuracy, precision, recall, F1 score etc.

[sushmith]

In this session we learnt about logistic regression and confusion matrix

[hrishikeshparasar]

GO_STP_5125

Today we learned about classification; then the difference between classification and regression; logistic regression and it's difference from linear regression; then Logistic regression and solved Iris classification problem and at last we learned about confusio matrix and accuracy

Thank you
Hrishikesh parasar

[rohitbadgujar]

GO_STP_9654 : In this session we learnt about 2 types of supervised machine learning classification and regression. we learnt details about classification in which we deals to find out categorical data and for regression its deals to find out continous data then we see logistics regression in detail and implement it by iris dataset in sklearn library. we also learnt about confusion matrix and accuracy determining techniques like accuracy, recall etc.

[MahendraSingh-gewz]

We Learnt:
1. Classification vs Regression
2. Logistic Regression
3. Logistics vs linear regression
1. Sigmoid function
2. Binary, Multinomial and Ordinal
3. Preprocessing: Data Scaling
4. Confusion matrix and accuracy

Thank you, ma'am


GO_STP_7372 | Mahendra Singh

[FizzFusion]

GO_STP_610
In today's session, we learnt about logistic regression and how it used to perform classification on data using the iris dataset. Also learned about confusion matrix and accuracy determining technique.

[moymaya]

Today's session was great.
Summary Class 10:
1) Classification
2) Classification vs Regression
3) What is Regression
4) Logistic Regression
5) Logistic Regression vs Linear regression
6) Iris dataset from Sklearn
7) Confusion Matrix
8) Accuracy

[DrNKSingh]

GO_STP_901:todaywe learned about how the logistics regression algorithm is used to perform classification on data practically using the iris flower dataset.

[charmikanani]

GO_STP_755:

We were introduced to classification problems. Understood the difference between regression and classification problems. We also built a logistic regression model using the Iris Dataset. We checked the accuracy of the model using the confusion matrix and accuracy score.

[BoomBoom-zrqu]

GO_STP_9672

it was a informative :- I have learn lots of things like
Whqt is classification, what is regression, logistics regression, flowers classification problems tec..in Python.
thank for such informative class.

[nandhinithokachichu]

GO_STP_10166:
earnt about supervised learning - classification. Within classification we saw logistic regression. Understood the difference between linear and logistic regression. The Iris dataset from Sklearn was used as example for logistic regression.We also learned about the confusion matrix and the various terms such as accuracy, precision and recall.
thank you:)

[prachimathur]

In this session we learned about what is classification, classification vs regression and logistic regression in phyton vs linear regression and iris flowers classifucation problem, confusion matrix and accuracy.

[tanushreesharma]

GO_STP_928
Today I have learned about Classification, Classification vs Regression, Regression, Logistic Regression, Logistic Regression vs Linear Regression, and Confusion Matrix and Accuracy.

[kajalrai]

GO_STP_4
In Today's session ew learnt about classification, regression, logistic regression vs linear regression