Python

How to handle categorical data in machine learning

How to handle categorical data in machine learning

Understanding Categorical Data and its Importance in Machine Learning Categorical data is a type of data that can be divided into distinct groups or categories. In machine learning, it is common to encounter categorical data in the form of labels, such as a classification problem where the output is a set of predefined categories. Handling categorical data is an important step in preprocessing your data for machine learning, as the algorithms used in machine learning often require numerical input. One of the most common ways to handle categorical data is through encoding. Encoding involves converting categorical data into a numerical…
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How to connect OpenAI api with python code

How to connect OpenAI api with python code

To connect OpenAI API with Python code, you will need to use the OpenAI Python library, which can be installed using pip: pip install openai You will also need to have an API key for the OpenAI service you want to use. You can get an API key by creating an account on the OpenAI website. Once you have the OpenAI library and an API key, you can use the following code as an example on how to connect the OpenAI API with Python: import openai # Set the API key openai.api_key = "YOUR_API_KEY" # Define the prompt prompt =…
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Random Forest Algorithm

Random Forest Algorithm

Random Forest is a robust machine-learning algorithm that is used for both classification and regression tasks. It is a type of ensemble learning method, which means that it combines multiple decision trees to create a more accurate and stable model. The mathematical intuition behind Random Forest is rooted in the concept of decision trees and bagging. A decision tree is a tree-like structure in which the internal nodes represent the feature(s) of the data, the branches represent the decision based on those features, and the leaves represent the output or class label. Each internal node in a decision tree represents…
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How to deal with outliers

How to deal with outliers

In this Notebook, we will describe how to deal with outliers #Importing the dataset import pandas as p import numpy as n import matplotlib.pyplot as plt import seaborn as sns from sklearn.datasets import load_boston import warnings warnings.filterwarnings('ignore') boston=load_boston() #it is stored as dictionary df= p.DataFrame(boston['data'],columns=boston['feature_names']) df.head() sns.distplot(df['RM']) #As we can see outliers sns.boxplot(df['RM']) Trimming outliers from the dataset def outliers(data): IQR=data.quantile(0.75)-data.quantile(0.25) lr=data.quantile(0.25)-(1.5*IQR) #lower range hr=data.quantile(0.70)+(1.5*IQR) #higher range return data.loc[~(n.where(data<lr,True,n.where(data>hr,True,False)))] outliers(df['RM']) #as we csn there is no outliers sns.boxplot(outliers(df['RM'])) #We can find outlier with using mean and standard deviation in case of IQR def outliers(data,k): lr=data.mean()-(data.std()*k) #where n is number hr=data.mean()+(data.std()*k)…
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Find out the Longest Path in a matrix

Find out the Longest Path in a matrix

Given an m-by-n matrix with positive integers, determine the length of the longest path of increasing within the matrix. For example, consider the input matrix:[1 2 34 5 67 8 9] The answer should be 5 since the longest path would be 1-2-5-6-9 def isValid(mat, i, j): return 0 <= i < len(mat) and 0 <= j < len(mat) def findLongestPath(mat, i, j): if not isValid(mat, i, j): return [] path = [] if i > 0 and mat[i - 1][j] - mat[i][j] == 1: path = findLongestPath(mat, i - 1, j) if j + 1 < len(mat) and mat[i][j…
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5 Amazing Python Tricks you should Know

5 Amazing Python Tricks you should Know

In this post, we'll talk about some tricks which come in handy when we're in urgent need. QR Code with Python pip install pyqrcode pip install pypng import pyqrcode from pyqrcode import QRCode import png # String which represents the QR code S= "www.geeksforgeeks.org" # Generate QR code url.pyqrcode.create(s) # Create and save the svg file naming "myqr.svg" url.svg("myqr.svg", scale = 8) # Create and save the png file naming "myqr.png" url.png ('myqr.png', scale = 6) Convert Images with Python pip install fpdf from fpdf import FPDF pdf = FPDF () # imagelist is the list with all image for…
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How to do Feature Encoding and Exploratory Data Analysis

How to do Feature Encoding and Exploratory Data Analysis

Categorical variables are those values that are selected from a group of categories or labels. For example, the variable Gender with the values of male or female is categorical, and so is the variable marital status with the values of never married, married, divorced, or widowed. In some categorical variables, the labels have an intrinsic order, for example, in the variable Student's grade, the values of A, B, C, or Fail are ordered, A being the highest grade and Fail the lowest. These are called ordinal categorical variables. Variables in which the categories do not have an intrinsic order are…
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What are Bias and Variance in Machine Learning

What are Bias and Variance in Machine Learning

As machine learning is increasingly used in applications, machine learning algorithms have gained more scrutiny. With larger data sets, various implementations, algorithms, and learning requirements, it has become even more complex to create and evaluate ML models since all those factors directly impact the overall accuracy and learning outcome of the model. This is further skewed by false assumptions, noise, and outliers. Machine learning models cannot be a black box. The user needs to be fully aware of their data and algorithms to trust the outputs and outcomes. Any issues in the algorithm or polluted data set can negatively impact the ML model. The main…
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Top Python Libraries You Should Know in 2022

Top Python Libraries You Should Know in 2022

Python libraries are a set of useful functions that eliminate the need to write code from scratch. There are currently more than 137,000 python libraries and they play a vital role in the development of machine learning, data science, data visualization, image and data manipulation applications, and more. Let's start with a brief introduction to the Python programming language and then dive right into the most popular Python libraries. The spirit of Guido Van Rossum - Python, which dates back to the 1980s, has become a passionate game changer. It is one of the most popular coding languages ​​today and…
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How to create a Digital Clock in Python With Tkinter

How to create a Digital Clock in Python With Tkinter

How to Make a Digital Clock with Python and Tkinter: We will now make a digital Clock. Here is its Demo. Importing Modules Import the following modules. from tkinter import * from tkinter.ttk import * from time import strftime import platform Here we have imported Tkinter, DateTime, and platform(for determining Operating System) Making a Tkinter Window We will now make a Tkinter window. main=Tk() main.title("Digital Clock in Python") main.geometry('1000x250') We have made a simple Tkinter window here. We have declared the title “Clock”. and set its size to ‘1000X250’ Creating Clock We will now Create a Digital Clock. Making a…
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