Python

Five Courses that can be finished in one week to advance Pandas skills

Five Courses that can be finished in one week to advance Pandas skills

๐Ÿ. ๐–๐ซ๐ข๐ญ๐ข๐ง๐  ๐„๐Ÿ๐Ÿ๐ข๐œ๐ข๐ž๐ง๐ญ ๐‚๐จ๐๐ž ๐ฐ๐ข๐ญ๐ก ๐ฉ๐š๐ง๐๐š๐ฌ: This course will build on your knowledge of Python and the panda's library and introduce you to efficient built-in pandas functions to perform tasks faster. Link:- Get the course here ๐Ÿ. ๐‰๐จ๐ข๐ง๐ข๐ง๐  ๐ƒ๐š๐ญ๐š ๐ฐ๐ข๐ญ๐ก ๐ฉ๐š๐ง๐๐š๐ฌ: In this course, you will learn to handle multiple DataFrames by combining, organizing, joining, and reshaping them using pandas. Get this course here ๐Ÿ‘. ๐’๐ญ๐ซ๐ž๐š๐ฆ๐ฅ๐ข๐ง๐ž๐ ๐ƒ๐š๐ญ๐š ๐ˆ๐ง๐ ๐ž๐ฌ๐ญ๐ข๐จ๐ง ๐ฐ๐ข๐ญ๐ก ๐ฉ๐š๐ง๐๐š๐ฌ: This course teaches you how to build pipelines to import data kept in common storage formats. Youโ€™ll use pandas to get data from a variety of sources, from spreadsheets of…
Read More
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…
Read More
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…
Read More
Which one to use – RandomForest vs SVM vs KNN?

Which one to use – RandomForest vs SVM vs KNN?

The basic steps to deciding which algorithm to use will depend on a number of factors. A few factors which one can look for are listed below: The number of examples in the training set.Dimensions of featured space.Do we have correlated features?Is overfitting a problem? These are just a few factors on which the selection of the algorithm may depend. Once you have the answers to all these questions, you can move ahead to decide the algorithm. SVM The main reason to use an SVM instead is that the problem might not be linearly separable. In that case, we will…
Read More
7 Mobile App Testing Ideas That Will Speed Up Your Releases.๏ฟผ

7 Mobile App Testing Ideas That Will Speed Up Your Releases.๏ฟผ

When it comes to apps, it's not just about the app itself. You need a platform that enables you to deliver an app that will delight your users and bring in revenue. Adhering to best practices is essential even if you're a one-person shop, so you can avoid any mishaps on launch day. Here are 7 mobile app testing ideas for your next release that will help smooth out every step of the process. 1. Automated App Testing One of the quickest and easiest ways to speed up your mobile app releases is to use automated testing tools. These tools…
Read More
Clustering & Visualization of Clusters using PCA

Clustering & Visualization of Clusters using PCA

Customer's Segmentation based on their Credit Card usage behavior Dataset for this notebook consists of the credit card usage behavior of customers with 18 behavioral features. Segmentation of customers can be used to define marketing strategies. Content of this Kernel: Data PreprocessingClustering using KMeansInterpretation of ClustersVisualization of Clusters using PCA # This Python 3 environment comes with many helpful analytics libraries installed # It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python # For example, here's several helpful packages to load in import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O (e.g.…
Read More
How do you count repeated words in a list in Python?

How do you count repeated words in a list in Python?

In this post, we will talk about how to count repeated words in python list. It can be done in many ways. Using collections.Counter() # Importing counter function. from collections import Counter words = ["a", "b", "a", "c", "c", "a", "c"] duplicate_dict = Counter(words) print(duplicate_dict)#to get occurence of each of the element. print(duplicate_dict['a'])# to get occurence of specific element. Output: Counter({'a': 3, 'c': 3, 'b': 1}) 3 Using count() letter = ["b", "a", "a", "c", "b", "a", "c",'a'] counting=letter.count('a') print(counting) Output: > 4 Hope this helps! Important Notice for college students If youโ€™re a college student and have skills in programming languages,…
Read More
What is the difference between artificial and convolutional neural networks?

What is the difference between artificial and convolutional neural networks?

Aย Convolutional Neural Network (ConvNet/CNN)ย is a Deep Learning algorithm that can take in an input image, assign importance (learnable weights and biases) to various aspects/objects in the image, and be able to differentiate one from the other. The pre-processing required in a ConvNet is much lower as compared to other classification algorithms. While in primitive methods filters are hand-engineered, with enough training, ConvNets have the ability to learn these filters/characteristics. The architecture of a ConvNet is analogous to that of the connectivity pattern of Neurons in the Human Brain and was inspired by the organization of the Visual Cortex. Individual neurons…
Read More
What is the VGG 19 neural network?

What is the VGG 19 neural network?

VGG 19ย is a convolutional neural network architecture that is 19 layers deep. The main purpose for which the VGG net was designed was to win theย ILSVRC imagenetย competition. Letโ€™s take a brief look at the architecture of VGG19. Input: The VGG-19 takes in an image input size of 224ร—224.Convolutional Layers: VGGโ€™s convolutional layers leverage a minimal receptive field, i.e., 3ร—3, the smallest possible size that still captures up/down and left/right. This is followed by a ReLU activation function. ReLU stands for rectified linear unit activation function, it is a piecewise linear function that will output the input if positive otherwise, the output is zero. Stride is…
Read More
What is clustering in machine learning?

What is clustering in machine learning?

Clusteringย is one of the most popular techniques inย unsupervised learningย where data is grouped based on the similarity of the data points. The basic principle behind clustering is the assignment of a given set of observations into subgroups or clusters such that observations present in the same clusters have a degree of similarity. It is a method ofย unsupervised learningย since there is no label attached to the data points. The machine has to learn the features and patterns all by itself without any given input-output mapping. There are several clustering in Machine Learning, Some common clustering algorithms are Centroid-based clustering:ย The first and foremost…
Read More