<?xml version="1.0" encoding="UTF-8" standalone="no"?><rss xmlns:atom="http://www.w3.org/2005/Atom" xmlns:blogger="http://schemas.google.com/blogger/2008" xmlns:gd="http://schemas.google.com/g/2005" xmlns:georss="http://www.georss.org/georss" xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" xmlns:openSearch="http://a9.com/-/spec/opensearchrss/1.0/" xmlns:thr="http://purl.org/syndication/thread/1.0" version="2.0"><channel><atom:id>tag:blogger.com,1999:blog-331977333533137262</atom:id><lastBuildDate>Fri, 10 Apr 2026 11:59:19 +0000</lastBuildDate><category>Python Tutorials</category><category>C Programming Tutorial</category><category>data analytics using Power BI</category><category>Data Science</category><category>प्रेरणादायी लेख</category><category>Oracle</category><category>SQL</category><category>प्रेरणादायी</category><category>BBA(CA). C++ Notes</category><category>Data Analytics using Python</category><category>MBA CET</category><category>MCA CET</category><category>BCA</category><category>BCS</category><category>MCA</category><category>Machine Learning</category><category>data analysis</category><category>AI</category><category>Data Security</category><category>पारंपरिक सण उत्सव</category><category>कोरोना आणि घडलेले बदल</category><category>ब्लॉग आणि ब्लॉगिंग</category><category>शिक्षक दिन</category><category>शब्द माझे सोबती</category><category>Management</category><category>NLP</category><category>Project</category><category>शैक्षणिक</category><category>C Programming Notes</category><category>C plus</category><category>C++</category><category>Data Analytics Using Tableau</category><category>Ekankika</category><category>IT Updates</category><category>Nested if  else Statement in C Language</category><category>Python</category><category>artificial intelligence</category><category>data visualization</category><category>jagtik mahila din</category><category>marathi articles</category><category>research</category><category>womens day</category><category>आभार प्रदर्शन</category><category>गुरू पौर्णिमा</category><title>मधूषाब्लॉग्स</title><description>वाचनातून प्रेरणा</description><link>https://madhushablogs.blogspot.com/</link><managingEditor>noreply@blogger.com (Dr.Manisha More)</managingEditor><generator>Blogger</generator><openSearch:totalResults>442</openSearch:totalResults><openSearch:startIndex>1</openSearch:startIndex><openSearch:itemsPerPage>25</openSearch:itemsPerPage><language>en-us</language><itunes:explicit>no</itunes:explicit><itunes:subtitle>वाचनातून प्रेरणा</itunes:subtitle><itunes:owner><itunes:email>noreply@blogger.com</itunes:email></itunes:owner><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-5495729767336959793</guid><pubDate>Thu, 02 Apr 2026 05:01:00 +0000</pubDate><atom:updated>2026-04-02T10:52:10.696+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">AI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><category domain="http://www.blogger.com/atom/ns#">Machine Learning</category><title>Recurrent Neural Network (RNN)</title><atom:summary type="text">&amp;nbsp;Introduction to&amp;nbsp;Recurrent Neural Network &amp;nbsp;RNN



&amp;nbsp;

A Recurrent
Neural Network (RNN) is a type of deep learning model designed to handle sequential
data. Unlike traditional neural networks, RNNs have memory, meaning
they can use information from previous inputs to influence the current output.

RNN
processes data step-by-step (time sequence) and remembers previous
information</atom:summary><link>https://madhushablogs.blogspot.com/2026/04/Introduction-to-Recurrent-Neural-Network-RNN.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://blogger.googleusercontent.com/img/a/AVvXsEi62Vj6jho0P-OYoPJkLj1XvcBcW1AQJ93-fdqajDqtT_XxNBVI18Oefg-FsNo3Goq924h2pdjnd7FyDrMSLhASHfg86ChJL8eAyW-hqUGgLiLXzNlZB6gsGZwhaPKR2wcABxjWEGVY1ch4SePcSHUP7qDw9PJM_uwvBdhIuciqJ7OGOdwZfUFQm0139PiO=s72-w525-h227-c" width="72"/><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-7602694775560328498</guid><pubDate>Mon, 23 Mar 2026 09:19:00 +0000</pubDate><atom:updated>2026-03-23T14:49:50.426+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">artificial intelligence</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><category domain="http://www.blogger.com/atom/ns#">Machine Learning</category><category domain="http://www.blogger.com/atom/ns#">NLP</category><title>Question Bank - Fundamentals of Machine Learning and NLP</title><atom:summary type="text">&amp;nbsp;Question Bank - Fundamentals of Machine Learning and NLPUnit 1:
Introduction to Machine Learning 


 A
     company is analyzing customer data to generate insights, build intelligent
     systems, and automate predictions. Explain how Data Science (data
     analysis), AI (intelligence), ML (learning from data), and DL (neural
     networks) are related in this scenario. 
 A
     business </atom:summary><link>https://madhushablogs.blogspot.com/2026/03/Question-Bank-Fundamentals-of-Machine-Learning-and-NLP.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-73105186087021088</guid><pubDate>Tue, 10 Mar 2026 06:16:00 +0000</pubDate><atom:updated>2026-03-10T11:46:08.303+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analysis</category><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><category domain="http://www.blogger.com/atom/ns#">data visualization</category><title>Extracting Date Components in Power BI Using DAX </title><atom:summary type="text">&amp;nbsp;Extracting Date Components in Power BI Using DAX (Year, Month, Quarter, Day, and Weekday)
Introduction:&amp;nbsp;
In Power BI Desktop, datasets often contain a Date column that stores complete date information. However, for proper analysis and dashboard creation, analysts usually need separate components of the date such as Year, Month, Quarter, Day, Day Name, Month Name, and Weekday.
Power BI </atom:summary><link>https://madhushablogs.blogspot.com/2026/03/Extracting-Date-Components-in-Power-BI-Using-DAX .html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-3985313338508854381</guid><pubDate>Sun, 08 Mar 2026 09:23:00 +0000</pubDate><atom:updated>2026-03-08T14:54:51.186+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">jagtik mahila din</category><category domain="http://www.blogger.com/atom/ns#">marathi articles</category><category domain="http://www.blogger.com/atom/ns#">womens day</category><category domain="http://www.blogger.com/atom/ns#">प्रेरणादायी</category><category domain="http://www.blogger.com/atom/ns#">प्रेरणादायी लेख</category><title>ती जन्म आणि सृजन</title><atom:summary type="text">ती…
ती जन्म घेते… आणि&amp;nbsp;नव्या जीवाला जन्म देण्याचं सौभाग्यही&amp;nbsp;तिचंच…ती सावरते, आणि तीच सगळं आवरते,&amp;nbsp;घराला आकारही तीच देते.ती एक… पण तिच्या भूमिका अनेक.कधी आई बनून मायेची सावली देते,कधी मुलगी बनून घराला आनंद देते.कधी पत्नी बनून आयुष्यभर साथ देते,&amp;nbsp;तर कधी बहीण बनून नात्यांना आधार देते.ती प्रत्येक भूमिकेत वेगळी जबाबदारी सांभाळते,प्रत्येक भूमिकेत वेगळ्या अपेक्षा पूर्ण करते…तरीही </atom:summary><link>https://madhushablogs.blogspot.com/2026/03/ti-janm-aani-srujan.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiur0rX5cWoLk9OOhdf1ZCWAvXYWMiGZNO-qL0TxB-4VyppDh9E6T33KY82nTjMZXPUT4FS5wlN1xNaLYEIy4IiWNP2sWqwvratRYdWTwAhkqWoj5j3CY327-ORfMXafij9Gbo3o0AfPnhQ1UgICEQqeU-eIQkM6TU7d_f4qysz2i2Nstk4yiRTeJ-18sTi/s72-w458-h489-c/Womens%20Day.png" width="72"/><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-3771006532447038948</guid><pubDate>Fri, 06 Mar 2026 04:40:00 +0000</pubDate><atom:updated>2026-03-26T10:34:07.276+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">AI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><category domain="http://www.blogger.com/atom/ns#">Machine Learning</category><category domain="http://www.blogger.com/atom/ns#">NLP</category><title>Introduction to Natural Language Processing (NLP)</title><atom:summary type="text">&amp;nbsp;Introduction to Natural Language Processing
(NLP)Introduction

Natural
Language Processing, commonly called NLP, is a branch of Artificial
Intelligence (AI), Machine Learning (ML), and Linguistics that
helps computers understand, interpret, process, and generate human language.
Human beings communicate through text and speech, but computers naturally
understand only numbers and structured </atom:summary><link>https://madhushablogs.blogspot.com/2026/03/Introduction-to-Natural-Language-Processing-NLP.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-568349369367168001</guid><pubDate>Tue, 03 Mar 2026 16:00:00 +0000</pubDate><atom:updated>2026-03-05T10:47:59.566+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">AI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><category domain="http://www.blogger.com/atom/ns#">Machine Learning</category><title>Association Rule Mining In Machine Learning</title><atom:summary type="text">&amp;nbsp;Association Rule Mining In Machine Learning

1) Introduction

Association
Rule Mining is a data-mining technique used to discover relationships
between items in large datasets. It answers questions like:


 “If a customer buys A,
     what else do they usually buy?”
 “Which services are commonly
     used together?”
 “What combinations of events
     happen frequently?”


It is
most famous </atom:summary><link>https://madhushablogs.blogspot.com/2026/03/Association-Rule-Mining-In-Machine-Learning.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-4025562541035607664</guid><pubDate>Mon, 02 Mar 2026 05:40:00 +0000</pubDate><atom:updated>2026-03-02T11:10:05.218+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">AI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><category domain="http://www.blogger.com/atom/ns#">Machine Learning</category><title>DBSCAN Algorithm of Unsupervised Machine Learning</title><atom:summary type="text">&amp;nbsp;DBSCAN Algorithm of Unsupervised Machine Learning

1️. Introduction to DBSCAN

DBSCAN stands for Density-Based
Spatial Clustering of Applications with Noise.

It is an unsupervised
machine learning clustering algorithm used to group data points based on density
(i.e., how closely packed data points are within a specific region) rather
than distance from a centroid (like K-Means).

DBSCAN is</atom:summary><link>https://madhushablogs.blogspot.com/2026/03/DBSCAN-Algorithm-of-Unsupervised-Machine-Learning.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://blogger.googleusercontent.com/img/a/AVvXsEi9zJ4AsmCdV9biYC8pXnPJCqs8vRL11n9gNpg-UXPzEglZO6XluWonDzZtDt2n90p1xO8pI_vLe9FECVRi_V_ZrrGaekYTuJSBcTYapVmIopaH6rluSzRjEfDfzLAOubFRG2XhLX295AE-XKY5p8-5NZDLr2uyIowSbvpPt_jf0_6Bft6PVD-pjCD39z6o=s72-w459-h219-c" width="72"/><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-4077893622946069649</guid><pubDate>Thu, 26 Feb 2026 17:25:00 +0000</pubDate><atom:updated>2026-02-26T22:59:02.695+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">AI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><category domain="http://www.blogger.com/atom/ns#">Machine Learning</category><title>Introduction to Hierarchical Clustering</title><atom:summary type="text">&amp;nbsp;Introduction to Hierarchical
Clustering

&#128313;
Definition

Hierarchical Clustering is an unsupervised
machine learning technique used to group similar data points into clusters
by building a tree-like structure called a dendrogram.

&#128313; Key Idea

Instead of fixing the number of clusters in
advance, hierarchical clustering:


 Creates
     clusters step-by-step
 Shows
     how clusters merge or </atom:summary><link>https://madhushablogs.blogspot.com/2026/02/Introduction-to-Hierarchical-Clustering.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://blogger.googleusercontent.com/img/a/AVvXsEiKoID_FHNuxGvE4CY22ljWwWNkytWZuoqoO6GP0ipCvRjT0ABRkFs8lNJlgpOc3Eb0pj88raomYeI0UFSLMgDjZWsKXQIglOaKW0E5paYEFSAQQZqIHhh3BPRE9f1-j7wfmkJrWe437KurOl8umNK15qJqRTkkBfPm0P28HoVzuoRYRE8rf8g4UL5NC27T=s72-w550-h321-c" width="72"/><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-6347692757275801031</guid><pubDate>Tue, 24 Feb 2026 16:17:00 +0000</pubDate><atom:updated>2026-03-05T13:55:29.580+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">AI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><category domain="http://www.blogger.com/atom/ns#">Machine Learning</category><title>K-Means Clustering</title><atom:summary type="text">&amp;nbsp;Introduction to Unsupervised Learning and ClusteringWhat is Unsupervised Learning?Unsupervised learning is a type of machine learning where the model is trained using unlabeled data. Unlike supervised learning, there is no predefined output or target variable. The algorithm independently identifies hidden patterns, structures, or relationships within the dataset.In unsupervised </atom:summary><link>https://madhushablogs.blogspot.com/2026/02/K-Means-Clustering.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://blogger.googleusercontent.com/img/a/AVvXsEhUAthWk1pW58eMG3mQMh_afOPXoFtNROlVGJRApoQONA_Y9W7cKIxiR-kUVHDZsnqVma9cgVCrrtC_B_xBCSwwuIzuVzCHLUSWcxZCa1LLZpULe6ZQv7Bx4_FyzXEVDdTYmA5Emmh0hHH8Ym0SD2G74loMbxKSJ6XCN_zNiHe60KeEHkZ6eSJ8WP4_E06-=s72-w489-h200-c" width="72"/><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-8255113345719458192</guid><pubDate>Tue, 17 Feb 2026 14:34:00 +0000</pubDate><atom:updated>2026-03-17T17:34:16.270+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analysis</category><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><title>Business Intelligence Using Power BI - Question Bank</title><atom:summary type="text">&amp;nbsp;Business Intelligence Using Power BIQuestion
Bank









Unit 1:
Introduction to Power BI

&lt;!--[if !supportLists]--&gt;1.&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;!--[endif]--&gt;Trace the historical development of Power BI
and discuss how it contributes to modern Business Intelligence practices.

&lt;!--[if !supportLists]--&gt;2.&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;!--[endif]--&gt;Describe the major capabilities and
</atom:summary><link>https://madhushablogs.blogspot.com/2026/02/Business-Intelligence-Using-Power-BI-Question-Bank.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-1469755049588704489</guid><pubDate>Sun, 15 Feb 2026 12:52:00 +0000</pubDate><atom:updated>2026-03-10T20:50:49.899+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analysis</category><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><title>Powe BI Video Tutorial(Power BI)</title><atom:summary type="text">&amp;nbsp;Powe BI Video Tutorial(Power BI)1. How to Start Power BI Desktop - First Project Sales data2. End to End Sales DashBoard&amp;nbsp;3. Power of Slicers in Power: Present Quick Insights from your large Datasets


4. Slicers in Power BI Indetail

4. Trend Analysis in Power BI/Line Chart in Power BI

5. Crimes Against Children Trend Analysis, Forecasting   


6. Geospatial and Demographic Analysis</atom:summary><link>https://madhushablogs.blogspot.com/2026/02/Powe-BI-Video-Tutorial-Power-BI.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://img.youtube.com/vi/v95NGqOT9uM/default.jpg" width="72"/><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-2976052786123238223</guid><pubDate>Thu, 12 Feb 2026 16:44:00 +0000</pubDate><atom:updated>2026-02-12T22:14:19.046+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analysis</category><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><title>Building KPI Dashboard in Power BI</title><atom:summary type="text">&amp;nbsp;

Building
KPI Dashboard in Power BI

Using Cyber Crime Data –
Step-by-Step GuideGo to Data Set







&amp;nbsp;1. Introduction to KPI

KPI (Key
Performance Indicator) is a measurable value that shows how effectively an objective is being
achieved.

In Power
BI, a KPI visual helps us:


 Show the current value
 Track trend over time
 Compare with a target
 Indicate performance using
     color</atom:summary><link>https://madhushablogs.blogspot.com/2026/02/Building-KPI-Dashboard-in-Power-BI.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-1518851081209652660</guid><pubDate>Sun, 11 Jan 2026 05:06:00 +0000</pubDate><atom:updated>2026-01-11T11:04:38.639+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analysis</category><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><category domain="http://www.blogger.com/atom/ns#">Data Analytics using Python</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><category domain="http://www.blogger.com/atom/ns#">research</category><title>Designing an Effective Questionnaire for Primary Data Collection</title><atom:summary type="text">&amp;nbsp;Understanding Primary and
Secondary Data in Research: A Foundation for Effective Data CollectionIntroductionIn any research study, case study, or academic
project,&amp;nbsp;data is the backbone of analysis and decision-making. The
accuracy, relevance, and reliability of research findings depend largely on the
type of data collected and the method used to collect it. Broadly, research
data is </atom:summary><link>https://madhushablogs.blogspot.com/2026/01/Designing-an-Effective-Questionnaire-for-Primary-Data-Collection.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>1</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-3878594633997448185</guid><pubDate>Wed, 07 Jan 2026 06:29:00 +0000</pubDate><atom:updated>2026-01-07T11:59:29.690+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analysis</category><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><category domain="http://www.blogger.com/atom/ns#">Data Science</category><title>Power BI Case Studies for MCA Students</title><atom:summary type="text">&amp;nbsp;Power BI Case Studies for MCA StudentsCase Study 01&amp;nbsp;Title:&amp;nbsp;Workplace Stress Across Different Industries
Problem Statement:Workplace stress has become a common issue across many industries due to factors such as high workload, poor work–life balance, long working hours, and limited control over job roles. These stress factors affect employee performance, job satisfaction, and </atom:summary><link>https://madhushablogs.blogspot.com/2026/01/Power-BI-Case-Studies-for-MCA-Students.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-1224656178740548831</guid><pubDate>Wed, 31 Dec 2025 07:09:00 +0000</pubDate><atom:updated>2025-12-31T13:36:27.194+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">प्रेरणादायी</category><category domain="http://www.blogger.com/atom/ns#">प्रेरणादायी लेख</category><category domain="http://www.blogger.com/atom/ns#">शब्द माझे सोबती</category><title>जीवन : गलतियाँ, सीख और सुधार — एक एल्गोरिदम</title><atom:summary type="text">&amp;nbsp;जीवन : गलतियाँ, सीख और सुधार — एक एल्गोरिदम
साल नाम का यह प्रोग्राम शुरू हुआ,
Day = 1 से काउंटर बढ़ता गया…Day++ होता हुआ
365 तक पहुँचा,हर दिन — एक नया डेटा पॉइंट।
कभी Positive Input,तो कभी Negative Value,कभी खुशी का Output,तो कभी दुःख का Exception Handling।
हर दिन खुलाएक नया Page / New Instance,नए अनुभवों की
डेटासेट में Entry होती गई।
खुशी देने वाले पलों ने
Accuracy बढ़ाई,और असफलताओं ने
</atom:summary><link>https://madhushablogs.blogspot.com/2025/12/blog-post_65.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://blogger.googleusercontent.com/img/a/AVvXsEhSbXdBqXuROwfvsSFbhO9c5e1IM9RRqqv1m0KrhlfpZpM_MTt7vpHNulPRAUYs2zFNRW7kD9A1tBEpTFOWgZHIf7fkxqJoXxs9slfQLGkBqDGlKWFwNahcpvbvuEV3rRlKguPO_VOC74f6tqif8oPXaT0SfeuYzHpXDp7JTNg4AMAJnwS2NoRzZn0dJ_HP=s72-w249-h240-c" width="72"/><thr:total>1</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-122797302911202900</guid><pubDate>Wed, 31 Dec 2025 06:57:00 +0000</pubDate><atom:updated>2025-12-31T12:59:03.531+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">प्रेरणादायी</category><category domain="http://www.blogger.com/atom/ns#">प्रेरणादायी लेख</category><category domain="http://www.blogger.com/atom/ns#">शब्द माझे सोबती</category><title>जीवन : चुका, शिकवण आणि सुधारणा – एक अल्गोरिदम</title><atom:summary type="text">&amp;nbsp;जीवन : चुका, शिकवण आणि सुधारणा – एक अल्गोरिदम
वर्ष नावाचा हा प्रोग्राम सुरू झाला,
Day = 1 पासून काउंटर वाढत गेला…Day++ होत
३६५ पर्यंत पोहोचला,प्रत्येक दिवस — एक नवीन डेटा पॉइंट.
कधी Positive Input,तर कधी Negative Value,कधी आनंदाचे Output,तर कधी दुःखाचे Exception Handling.
दररोज उघडलीएक नवीन Page / New Instance,नवीन अनुभवांची
डेटासेटमध्ये Entry झाली.
आनंद दिलेल्या क्षणांनी
Accuracy वाढवली,</atom:summary><link>https://madhushablogs.blogspot.com/2025/12/blog-post_31.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://blogger.googleusercontent.com/img/a/AVvXsEgUuC1DyZBfEbVZfnm3JZdKkyNeHHxlMvDWM7By6Cl7BDFtVK_i14HPFfk1Vb5ef22hyS994lUqkCQvrQarsP8wDguINkEl0SQJhUlqFRyzGYE2qUyd_eNxyvcq6JescMP4FvbGK5oPCWXpJvPt6AdZiDQXDzOiOZha3LFOmf9kHwDL0e3juNRWbJFSL-EU=s72-w265-h278-c" width="72"/><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-2094959130963985483</guid><pubDate>Thu, 25 Dec 2025 05:53:00 +0000</pubDate><atom:updated>2025-12-26T22:37:47.098+05:30</atom:updated><title>शिक्षक भी इंसान है</title><atom:summary type="text">&amp;nbsp;"शिक्षक भी इंसान है”
एक दिन था…&amp;nbsp;जब मन बहुत खुश था,आँखों में सपने थे,&amp;nbsp;और दिल में गर्व—क्योंकि मैं एक विश्वविद्यालय का हिस्सा बनने जा रही थी।
चुना गया था मुझे&amp;nbsp;मेहनत से,इंटरव्यू की कसौटी पर,प्रक्रियाओं की पारदर्शिता से।
पहले दिन,&amp;nbsp;वरिष्ठों से संवाद हुआ,अनुशासन, समर्पण और संकल्प—इन तीन स्तंभों पर खड़ीएक आदर्श संस्था दिखी।
हर दिन लगता था—“हम किसी साधारण जगह नहीं,एक मूल्यवान </atom:summary><link>https://madhushablogs.blogspot.com/2025/12/blog-post.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiis_tdqObi2kGKXZ41eHerXZfUbM7pqRZkGyZUAPsI2RWvO2_o1loJXLSyWMRnzKL7a6zGvWsXCvWLCBqAUh8_Bwr7IsxsDpVnm60iW8ITypPki7OUsxdJfbU_dtJYeAKOgTIr2aXDm435WjtYRkRat92dHgh9WB4Ev6F8jOZ30KmMb87Hy9QgJdQHa27L/s72-w397-h320-c/Green%20and%20Brown%20Illustrative%20Teachers'%20Day%20Instagram%20Post%20(2).png" width="72"/><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-8595468960869351453</guid><pubDate>Mon, 08 Dec 2025 06:48:00 +0000</pubDate><atom:updated>2025-12-10T15:28:50.842+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">Ekankika</category><category domain="http://www.blogger.com/atom/ns#">प्रेरणादायी</category><category domain="http://www.blogger.com/atom/ns#">प्रेरणादायी लेख</category><title>“मी येऊ का या जगात, आई?”</title><atom:summary type="text">&amp;nbsp;शीर्षक : संवेदना

प्रा. डॉ. मनिषा पाटील-मोरे

कालावधी : 35–40 मिनिटे
थीम : सामाजिक, भावनिक, महिला
सुरक्षा, जागृती
पात्रे : 12–15







⭐ पात्रसूची


 आई — गर्भवती, संवेदनशील पण नंतर कणखर
 अजून न जन्मलेली मुलगी —
     Voiceover
 निवेदक
 लहान मुलीचे प्रतीक (4 वर्षांची) — निःशब्द
     अभिनय
 नराधमाची सावली (Shadow
     Actor)
 समाजगट (4–6 जण)
 देव/न्यायाचा आवाज — Voiceover
 TV
     Anchor
 </atom:summary><link>https://madhushablogs.blogspot.com/2025/12/mi-yevu-ka-ya-jagat-aayi     .html</link><author>noreply@blogger.com (Dr.Manisha More)</author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" height="72" url="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjY2Rp-gtwJX5cE9eS3fLgpU2CxB2QDGVUGutn_rcLfew764rLH2v1UO6U0Gthd0jWaKIhfV6zJPn2gjJj2mJV2sm0WLn_FSkz2g1jIgw7lvMHYHEKausMXRxJn3I89cHgwHo4avVZmw0o9GuQdfqo8Gm9uskAxwyha6P61KUQQ68M85IMbQIGYvQY2xe2S/s72-w479-h483-c/happy%20mother's%20%20day%20(Poster).png" width="72"/><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-7239331859026373708</guid><pubDate>Wed, 24 Sep 2025 08:16:00 +0000</pubDate><atom:updated>2025-09-24T16:10:04.128+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><title>Clustering in Power BI</title><atom:summary type="text">&amp;nbsp;Clustering in Power BI: A Step-by-Step Guide
Clustering is a data analysis technique used to group similar data points together based on their characteristics. In Power BI, clustering helps you identify patterns, segment data, and make better decisions. This guide explains two approaches: using Power BI’s built-in clustering and using the Python visual.

1. Clustering in Power BI (Without </atom:summary><link>https://madhushablogs.blogspot.com/2025/09/Clustering-in-Power-BI.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-5300202426167158768</guid><pubDate>Tue, 23 Sep 2025 10:07:00 +0000</pubDate><atom:updated>2025-09-23T15:37:04.473+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><title>Power BI Project on Indian School Education Statistics </title><atom:summary type="text">&amp;nbsp;Power BI Project on Indian School Education Statistics&amp;nbsp;Problem Statement (Download Dataset)
Educational development is one of the critical indicators of a nation’s growth. Despite significant policy interventions in India, disparities persist across states, gender, and different educational levels. This dataset provides information on Gross Enrolment Ratios (GER) of boys, girls, and </atom:summary><link>https://madhushablogs.blogspot.com/2025/09/Power-BI-Project-on-Indian-School-Education-Statistics .html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-6336986328388340573</guid><pubDate>Mon, 15 Sep 2025 17:22:00 +0000</pubDate><atom:updated>2025-09-15T22:52:23.986+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><title>How to Use  Python in Power BI</title><atom:summary type="text">Introduction to Python Visuals in Power BI
Power BI provides an option to use Python scripts directly inside visuals. This feature allows you to leverage the data analysis, statistical, and visualization power of Python within Power BI dashboards.
When you add a Python visual from the Visualizations pane:


Power BI passes the selected fields from your dataset into a pandas DataFrame named </atom:summary><link>https://madhushablogs.blogspot.com/2025/09/How-to-Use-Python-in-Power-BI.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-8880037673149795997</guid><pubDate>Mon, 15 Sep 2025 10:29:00 +0000</pubDate><atom:updated>2025-09-25T22:17:49.576+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><title>Question Bank : Power BI</title><atom:summary type="text">&amp;nbsp;Question BankUnit : 01

&lt;!--[if !supportLists]--&gt;1.&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;!--[endif]--&gt;Explain the role of Power BI in modern business intelligence and compare
the features of Power BI Desktop and Power BI Service.

&lt;!--[if !supportLists]--&gt;2.&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;!--[endif]--&gt;Discuss the importance of different visualization types in Power BI and
explain with examples how charts </atom:summary><link>https://madhushablogs.blogspot.com/2025/09/Question-Bank-Power-BI.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>1</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-6903447865372607529</guid><pubDate>Mon, 15 Sep 2025 10:10:00 +0000</pubDate><atom:updated>2025-09-19T15:27:34.521+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><title>Power BI project on Healthcare Dataset</title><atom:summary type="text">&amp;nbsp;Power BI project on Healthcare DatasetProblem Statement
In today’s data-driven environment, organizations across industries are challenged not only to collect vast amounts of data but also to transform it into actionable insights that support strategic decision-making. Traditional reporting techniques often fall short in providing interactive, real-time, and predictive capabilities. As a </atom:summary><link>https://madhushablogs.blogspot.com/2025/09/Power-BI-project-on-Healthcare-Dataset.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-6694402418373290925</guid><pubDate>Thu, 04 Sep 2025 06:30:00 +0000</pubDate><atom:updated>2025-09-04T12:01:30.664+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><title>A Power BI Project on Kidnapping &amp; Abduction Dataset in India </title><atom:summary type="text">A Power BI Project on Kidnapping &amp;amp; Abduction Dataset in India&amp;nbsp;Download Dataset &#128073;&#128073;&#128073;&#128073;Kidnapping &amp;amp; Abduction&amp;nbsp;Dataset Description
This dataset represents child victims of kidnapping &amp;amp; abduction cases across different cities. The victims are classified into three age groups:


Below 6 Years


6 to 12 Years


12 to 16 Years


For each age group, victims are further divided by </atom:summary><link>https://madhushablogs.blogspot.com/2025/09/A Power BI-Project-on-Kidnapping--Abduction-Dataset-in-India .html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item><item><guid isPermaLink="false">tag:blogger.com,1999:blog-331977333533137262.post-1798896268771546029</guid><pubDate>Tue, 02 Sep 2025 05:33:00 +0000</pubDate><atom:updated>2025-09-02T12:04:34.809+05:30</atom:updated><category domain="http://www.blogger.com/atom/ns#">data analytics using Power BI</category><title>Analysis of All Types of Crimes in India in Power BI</title><atom:summary type="text">&amp;nbsp;Analysis of All Types of Crimes in India in Power BIProblem Statement:&amp;nbsp;The study aims to analyze the trends, patterns, and variations in IPC crimes across India between 2020 and 2022. Using Power BI for visualization and analytics, the research focuses on understanding the rise and fall of different crime categories, their relative contribution to overall IPC crimes, and the </atom:summary><link>https://madhushablogs.blogspot.com/2025/09/Analysis-of-All-Types-of-Crimes-in-India-in-Power-BI.html</link><author>noreply@blogger.com (Dr.Manisha More)</author><thr:total>0</thr:total></item></channel></rss>