![]() ![]() Gensim Tutorial – A Complete Beginners Guide.101 NLP Exercises (using modern libraries).Text Summarization Approaches for NLP – Practical Guide with Generative Examples.Complete Guide to Natural Language Processing (NLP) – with Practical Examples.How to implement Linear Regression in TensorFlow.How to use tf.function to speed up Python code in Tensorflow.TensorFlow vs PyTorch – A Detailed Comparison.One Sample T Test – Clearly Explained with Examples | ML+.Understanding Standard Error – A practical guide with examples.T Test (Students T Test) – Understanding the math and how it works.Mahalanobis Distance – Understanding the math with examples (python).How to implement common statistical significance tests and find the p value?.What is P-Value? – Understanding the meaning, math and methods.Chi-Square test – How to test statistical significance?.Vector Autoregression (VAR) – Comprehensive Guide with Examples in Python.Time Series Analysis in Python – A Comprehensive Guide with Examples.ARIMA Model – Complete Guide to Time Series Forecasting in Python.Augmented Dickey Fuller Test (ADF Test) – Must Read Guide.What does Python Global Interpreter Lock – (GIL) do?.Lambda Function in Python – How and When to use?.Python Yield – What does the yield keyword do?.cProfile – How to profile your python code.Python Collections – An Introductory Guide.Requests in Python Tutorial – How to send HTTP requests in Python?.datetime in Python – Simplified Guide with Clear Examples.Python Logging – Simplest Guide with Full Code and Examples.Python Regular Expressions Tutorial and Examples: A Simplified Guide.Python Explained – How to Use and When? (Full Examples).Parallel Processing in Python – A Practical Guide with Examples.List Comprehensions in Python – My Simplified Guide.Object Oriented Programming (OOPS) in Python.Python Module – What are modules and packages in python?.Iterators in Python – What are Iterators and Iterables?.Generators in Python – How to lazily return values only when needed and save memory?.Decorators in Python – How to enhance functions without changing the code?.How to deal with Big Data in Python for ML Projects (100+ GB)?.You can find the complete documentation for the regplot() function here. #create scatterplot with regression line and confidence interval lines You can choose to show them if you’d like, though: import seaborn as sns Note that ci=None tells Seaborn to hide the confidence interval bands on the plot. You can also use the regplot() function from the Seaborn visualization library to create a scatterplot with a regression line: import seaborn as sns For example, here’s how to change the individual points to green and the line to red: #use green as color for individual points #add linear regression line to scatterplotįeel free to modify the colors of the graph as you’d like. #obtain m (slope) and b(intercept) of linear regression line The following code shows how to create a scatterplot with an estimated regression line for this data using Matplotlib: import matplotlib.pyplot as plt This tutorial explains both methods using the following data: import numpy as np Often when you perform simple linear regression, you may be interested in creating a scatterplot to visualize the various combinations of x and y values along with the estimation regression line.įortunately there are two easy ways to create this type of plot in Python. ![]()
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