Data Science

Data Science and A.I. – Quartiles, Deciles, and Percentiles

Artificial Intelligence, Data Handling, Deep Learning, Generative A., Generative A. I., Machine Learning, Probability and Statistics, Research and Development, Statistics /

“`html PostNetwork Academy guides us through three crucial statistical measures: Quartiles, Deciles, and Percentiles These measures are used to divide a data distribution into equal parts, making them essential tools in data analysis. Hello everyone! Welcome to another educational post from PostNetwork Academy. I’m Bindeshwar, and before we begin, make sure to follow us on […]

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variance

Data Science and A.I. : Measures of Dispersion : Variance of Continuous Freq. Distribution

Artificial Intelligence, Data Handling, Machine Learning, Probability and Statistics, Statistics /

In this post, we dive into one of the core statistical concepts used in data science and artificial intelligence—calculating the variance of a continuous frequency distribution. Breaking down the steps If you have data distributed across class intervals with frequencies, the goal is to find the variance. The video explains the columns in the table:

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Poisson Distibution

Poisson Distribution in Statistics and Mathematics

Uncategorized /

Poisson Distribution- The Poisson distribution is defined by a single parameter, usually denoted by λ (lambda), which represents the average rate of occurrence of the events. The probability mass function (PMF) of the Poisson distribution is given in the image above. Poisson Distribution is Limiting Case of Binomial Distribution It’s worth noting that the Poisson

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Random Variable and Probability Mass Function

Random Variable and Probability Mass Function

Leave a Comment / Machine Learning, Mathematics, Probability and Statistics, Statistics /

Random variable   is a very  important concept in probability, statistics, data science and machine learning, one must  learn concept of random variable and related concepts. In this post, I have explained random variable and probability mass function that will help you to have basic understanding of  random variable and probability mass function. To understand random

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massachusetts institute of technology

M. I. T. Researchers Developed A. I. Model Which Can Locate Cancer

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Researchers at Massachusetts Institute of Technology    with Dana-Farber Cancer Institute  have developed a machine learning model  which can locate  the origin of the cancer.  Researchers developed machine learning model which can analyze sequence of  400  genes and predict that where is tumor located. Researchers took data of 900 patients  and trained machine learning model

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Understand classification Problem in Machine Learning

Understand classification Problem in Machine Learning

Leave a Comment / Machine Learning /

Basically, there are four types of machine learning algorithms. 1- Supervised Learning Algorithms- In supervised  learning, values of  features and labels or classes are given. Further, Supervised learning algorithms are of two types. 1.1- Regression- In regression numerical values are predicted. 1.2-Classification In classification, labels  are predicted. 2-Unsupervised Learning Algorithms In unsupervised learning, instances have

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Pandas Series Functions min(), max(), mean(), median() and mode()

Leave a Comment / Data Handling, Machine Learning, Programming, Python /

Panda’s Series- In the last post, I explained how to create a panda’s series. Further,  a pandas series has a lot of   you often need to analyze, visualize and clean data.  In this post, I will be explaining min(), max(), mean(), median(), and mode functions. min() Function- import pandas as pd lst=[2, 4, 6, 8,

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K-Means-Clustering

K-Means Clustering Algorithm in Machine Learning

Leave a Comment / Machine Learning, Python /

K-Means clustering is an unsupervised   machine learning algorithm which partitions n instances into k clusters by similarity. As K-Means clustering is an unsupervised learning algorithm, therefore instances will not have labels. As  K-Means clustering  is an unsupervised learning algorithm, training instances will not have labels. Furthermore, to make you understand K-Means clustering algorithm, I will

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K-Nearest-Neighbor-Algorithm

K-Nearest Neighbors Algorithm in Machine Learning

Leave a Comment / Machine Learning, Python /

K-Nearest Neighbors algorithm (KNN) K-Nearest Neighbors algorithm (KNN) is a very important supervised machine learning algorithm and one should start from this algorithm. It is easy to understand compare to other algorithms and does not involve complex mathematical concepts. In this post, I will explain k-Nearest Neighbors algorithm using Irish flowers data set.   From

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