tag:blogger.com,1999:blog-331977333533137262Thu, 01 Oct 2026 07:23:44 +0000Python TutorialsC Programming TutorialData Sciencedata analytics using Power BIप्रेरणादायी लेखAIOracleSQLartificial intelligenceDeep LearningNLPप्रेरणादायीMachine LearningBBA(CA). C++ NotesData Analytics using PythonMBA CETMCA CETBCABCSMCAdata analysisData Securityपारंपरिक सण उत्सवMLकोरोना आणि घडलेले बदलब्लॉग आणि ब्लॉगिंगशिक्षक दिनशब्द माझे सोबतीManagementProjectgenerative aitransformerशैक्षणिकBERTC Programming NotesC plusC++CNNData Analytics Using TableauEkankikaGANGRUIT UpdatesImage ClassificationLIMELSTMNER named entity recognitionNested if else Statement in C LanguagePythonSHAPdata visualizationexplainable AIjagtik mahila dinmarathi articlesresearchsentimental analysis of customer feedbacktime series forecastingwomens dayआभार प्रदर्शनगुरू पौर्णिमावाचनातून प्रेरणाhttps://madhushablogs.blogspot.com/noreply@blogger.com (Dr.Manisha More)Blogger474125en-usnoवाचनातून प्रेरणाnoreply@blogger.comtag:blogger.com,1999:blog-331977333533137262.post-2736318510068014464Sat, 26 Sep 2026 04:22:32 +00002026-09-26T09:52:32.613+05:30AIartificial intelligenceDeep Learningexplainable AIgenerative aiLIMENLPSHAP Explainable Artificial Intelligence (XAI) Understanding CNN Predictions Using Grad-CAM, LIME and SHAPIntroduction to Explainable Artificial IntelligenceArtificial Intelligence and Deep Learning models are increasingly used for image classification, medical diagnosis, financial analysis, recommendation systems, fraud detection, autonomous systems, and many other applications. These models https://madhushablogs.blogspot.com/2026/09/Explainable-Artificial-Intelligence-XAI.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-6874147194572878655Fri, 25 Sep 2026 17:49:24 +00002026-09-25T23:19:24.186+05:30 Integrated NLP Pipeline for Linguistic and Sentiment Analysis of TextIntroductionNatural Language Processing (NLP) is a branch of Artificial Intelligence that enables computers to process, understand, and analyze human language. A text contains different types of information. It contains individual words, grammatical information, names of people, organizations and places, and it may also https://madhushablogs.blogspot.com/2026/09/integrated-nlp-pipeline-for-linguistic.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-6509196270643741624Thu, 24 Sep 2026 06:15:53 +00002026-09-24T12:01:56.518+05:30AIartificial intelligenceDeep LearningGANgenerative aiNLP Generative Models: Autoencoders, Variational Autoencoders, GANs and Their ApplicationsIntroduction to Generative ModelsGenerative Models are Artificial Intelligence models that learn the underlying patterns and characteristics of existing data and use this knowledge to generate new data similar to the original data.Unlike traditional models that mainly classify or predict, generative modelshttps://madhushablogs.blogspot.com/2026/09/Generative-Models-Autoencoders-Variational-Autoencoders-GANs-and-Their-Applications.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-7914065614122934367Wed, 23 Sep 2026 05:18:33 +00002026-09-23T10:48:33.381+05:30AIartificial intelligenceDeep LearningNER named entity recognitionNLPNamed Entity Recognition (NER) on Apple Product ReviewsProblem Statement Customer reviews contain useful information about products, prices, organizations, and other important entities. The objective of this practical is to apply Named Entity Recognition (NER) to Apple product reviews and automatically identify and extract these important entities from the review text.Download Apple.txt Dataset&https://madhushablogs.blogspot.com/2026/09/Named-Entity-Recognition-NER-on-Apple-Product-Reviews.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-32485478497892051Sun, 20 Sep 2026 17:38:52 +00002026-09-20T23:08:52.599+05:30AIartificial intelligenceBERTDeep LearningNLPtransformer Sentiment Analysis Using Pre-Trained BERT Problem Statement Develop a Transformer-based sentiment analysis model using a pre-trained DistilBERT model to classify IMDb movie reviews as Positive or Negative. The model will use the Hugging Face Transformers library for tokenization and fine-tuning and will be evaluated using suitable classification metrics. Dataset Description The IMDb Movie https://madhushablogs.blogspot.com/2026/09/Sentiment-Analysis-Using-Pre-Trained-BERT.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-8205477825034261753Sun, 20 Sep 2026 17:35:50 +00002026-09-20T23:05:50.158+05:30AIartificial intelligenceDeep LearningNLPsentimental analysis of customer feedback NLP-Based Sentiment Analysis of E-Commerce Customer FeedbackProblem Statement E-commerce websites receive large amounts of customer feedback about products and services. Manually analyzing this feedback is time-consuming. The objective of this practical is to apply Natural Language Processing (NLP) techniques to preprocess customer feedback and perform sentiment analysis to identify https://madhushablogs.blogspot.com/2026/09/NLP-Based-Sentiment-Analysis-of-E-Commerce-Customer-Feedback.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-5221882323059164204Wed, 09 Sep 2026 16:12:42 +00002026-09-16T09:55:11.886+05:30AIartificial intelligenceDeep Learningtime series forecastingtransformer Transformer-Based Household Electric Power Consumption Forecasting Problem Statement Develop a Transformer-based time-series forecasting model to predict household electric power consumption using historical electricity usage data. The model will use the previous 60 minutes of Global Active Power consumption to predict the consumption for the next minute. The model's forecasting performancehttps://madhushablogs.blogspot.com/2026/09/Transformer-Based-Household-Electric-Power-Consumption-Forecasting.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-8348381031067752515Fri, 04 Sep 2026 08:24:43 +00002026-09-08T12:36:24.370+05:30AIartificial intelligenceDeep LearningGRULSTMGRU-based Time-Series Forecasting Model to Predict Household Electric Power ConsumptionProblem Statement Develop a GRU-based time-series forecasting model to predict household electric power consumption using historical electricity usage data and evaluate its performance using MAE and RMSE.Download Dataset: Household_Power_Consumption.txtDataset Description The dataset contains measurements of https://madhushablogs.blogspot.com/2026/09/GRU-based-Time-Series-Forecasting-Model to-Predict-Household-Electric-Power-Consumption.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-7951460309409570076Tue, 01 Sep 2026 06:56:40 +00002026-09-01T12:26:40.709+05:30AIartificial intelligenceData ScienceDeep Learning NIFTY 50 Closing Price Prediction Using Long Short-Term Memory (LSTM)Problem StatementDevelop an LSTM-based time-series forecasting model to predict the next trading day's NIFTY 50 closing price using historical closing-price data. The model should learn temporal patterns from previous trading days and evaluate its forecasting performance using suitable regression metrics.Dataset NameNIFTY https://madhushablogs.blogspot.com/2026/09/NIFTY-50-Closing-Price-Prediction-Using-Long-Short-Term-Memory-LSTM.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-988225569993790251Tue, 01 Sep 2026 04:12:25 +00002026-09-02T18:30:20.572+05:30AIartificial intelligenceData ScienceDeep LearningNLPLong Short-Term Memory (LSTM) Networks1. IntroductionRecurrent Neural Networks (RNNs) are designed to process sequential or time-series data by remembering information from previous time steps. They work well for short sequences but struggle when the sequence becomes longer.Long Short-Term Memory (LSTM) is an advanced type of RNN that overcomes this limitation by learning what information should https://madhushablogs.blogspot.com/2026/08/Long-Short-Term-Memory-LSTM-Networks.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-5730874380872804942Wed, 26 Aug 2026 05:04:13 +00002026-08-26T10:34:13.262+05:30AIartificial intelligenceDeep LearningNLP Develop a Simple Recurrent Neural Network (RNN) model to predict the next day's minimum temperatureProblem Statement Develop a Simple Recurrent Neural Network (RNN) model to predict the next day's minimum temperature using the temperature values of the previous 7 days. Evaluate the model using RMSE and compare actual and predicted temperatures graphically. Download DatasetDataset https://madhushablogs.blogspot.com/2026/08/Develop-a-Simple-Recurrent-Neural-Network-RNN-model-to-predict-the-next-days-minimum-temperature.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-7655045706365923049Tue, 25 Aug 2026 08:54:36 +00002026-08-25T14:24:36.373+05:30AIartificial intelligenceDeep Learning RNN Model to Predict Airline Passenger CountsProblem StatementTo develop a Simple RNN model using the AirTrafficMovement dataset to predict the next month's total passenger traffic based on the previous 12 months' passenger counts.Dataset DescriptionThe AirTrafficMovement dataset contains monthly airport traffic information related to aircraft movements, passenger traffic, air mail, and https://madhushablogs.blogspot.com/2026/08/RNN-Model-to-Predict-Airline-Passenger-Counts.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-94548763172519500Sat, 22 Aug 2026 04:40:50 +00002026-08-22T10:13:26.025+05:30AIartificial intelligenceData ScienceDeep Learning Introduction to Optimizers In Deep Learning, an optimizer is an algorithm used to update the weights and biases of a neural network to minimize the loss (error) during training. After Backpropagation calculates the gradients, the optimizer uses these gradients to determine how the weights should be changed. Training Flow: Feed Forward → Prediction → Loss → Backpropagation → Gradient → https://madhushablogs.blogspot.com/2026/08/Introduction-to-Optimizers.htmlnoreply@blogger.com (Dr.Manisha More)1tag:blogger.com,1999:blog-331977333533137262.post-7481477768804902771Fri, 31 Jul 2026 05:11:23 +00002026-08-07T14:00:16.333+05:30AIartificial intelligenceCNNDeep LearningImage Classification Image Classification Using Convolutional Neural Networks (CNN) with Fashion MNIST DatasetProblem StatementThe objective of this practical is to build a Convolutional Neural Network (CNN) to automatically classify grayscale images of clothing into one of ten fashion categories using the Fashion MNIST dataset.ObjectiveUnderstand the basic architecture of CNN.Load and preprocess the Fashion https://madhushablogs.blogspot.com/2026/07/Image-Classification-Using-Convolutional-Neural-Networks-CNN-with-Fashion-MNIST-Dataset.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-6578348387859640248Mon, 27 Jul 2026 04:05:06 +00002026-07-27T09:35:06.287+05:30AIartificial intelligenceData ScienceDeep LearningMachine LearningNLP ANN - for Customer Subscription Prediction Using the Bank Marketing DatasetProblem Statement Develop an Artificial Neural Network (ANN) model to predict whether a customer will subscribe to a term deposit based on customer demographic, financial, and marketing campaign information.  Download DatasetDataset Summary ParameterValueDataset NameBank Marketing DatasetSourceUCI Machine https://madhushablogs.blogspot.com/2026/07/ann-for-customer-subscription.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-8797652639993510068Sat, 25 Jul 2026 04:22:37 +00002026-07-25T09:52:37.786+05:30AIartificial intelligenceData ScienceDeep LearningNLPDiabetes Prediction Using Artificial Neural Network (ANN) Problem Statement Develop an Artificial Neural Network (ANN) model to predict whether a patient is diabetic or non-diabetic using the Pima Indians Diabetes Dataset. The model should be trained using patient health parameters and evaluated using appropriate performance metrics. Dataset Description Dataset Name: Pima Indians Diabetes https://madhushablogs.blogspot.com/2026/07/Diabetes-Predict-on-Using-Artificial-Neural-Network-ANN.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-1799321321290159786Wed, 22 Jul 2026 05:10:47 +00002026-07-22T10:43:08.137+05:30AIartificial intelligenceData ScienceDeep LearningMachine LearningNLP Introduction to CNN and Its Applications in Computer Vision 1. Introduction Humans can easily recognize objects, faces, animals, vehicles, handwritten text, and different activities in images. For example, when we see an image of a cat, we can identify it even when its position, size, colour, background, or direction changes. For a computer, an image is not directly understood as a cat, https://madhushablogs.blogspot.com/2026/07/Introduction-to-CNN-and-Its-Applications-in-Computer-Vision.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-7432349194335592598Tue, 21 Jul 2026 05:19:48 +00002026-07-21T10:49:48.235+05:30 Deep Feed Forward Neural Network with Backpropagation for Student Placement Prediction Problem Statement Student placement prediction is an important application of Artificial Intelligence and Deep Learning. Educational institutions often need to identify whether a student is likely to be placed based on academic and skill-related factors. Traditional prediction methods rely on manual https://madhushablogs.blogspot.com/2026/07/deep-feed-forward-neural-network-with.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-6781262821615757254Tue, 21 Jul 2026 05:14:08 +00002026-07-21T13:45:54.713+05:30AIartificial intelligenceData ScienceDeep LearningNLP Stochastic Gradient Descent in Deep Neural NetworksReal-Life ExampleConsider a hospital where a patient's medical test results, such as radius, texture, perimeter, and area of a breast tumor, are collected. These features are provided as input to the neural network.Input features → Hidden layers → Benign or Malignant prediction If the model makes an incorrect prediction, the error is https://madhushablogs.blogspot.com/2026/07/ Stochastic-Gradient-Descent-in-Deep-Neural-Networks.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-7804252468746046063Mon, 20 Jul 2026 07:32:13 +00002026-07-22T21:40:41.658+05:30AIartificial intelligenceData ScienceDeep LearningMachine LearningNLP Path Finding in a Maze Using the A Search AlgorithmProblem StatementPathfinding is an important Artificial Intelligence problem in which an agent must find the shortest path from a starting position to a goal position while avoiding obstacles.In this practical, the A* Search Algorithm is implemented using Python to solve a pathfinding problem in a two-dimensional maze. A* selects the most https://madhushablogs.blogspot.com/2026/07/Path Finding in a Maze Using the-A-star-Search-Algorithm.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-6819381766810289689Fri, 17 Jul 2026 04:04:37 +00002026-07-17T09:56:53.214+05:30AIartificial intelligenceData ScienceDeep LearningMachine LearningNLP Feed Forward Neural Network (FFNN) Understanding Information Flow in Artificial Neural Networks Introduction In the previous sessions, we learned about Artificial Neural Networks (ANNs), Single-Layer Perceptrons, Multi-Layer Perceptrons, and why hidden layers are required to solve non-linear problems such as XOR and XNOR. An important question now arises: How does information actually https://madhushablogs.blogspot.com/2026/07/Feed-Forward-Neural-Network-FFNN.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-2667186102911089133Thu, 16 Jul 2026 05:53:33 +00002026-07-16T11:23:33.832+05:30AIartificial intelligenceData ScienceDeep LearningNLP Path Finding in a Maze Using Breadth-First Search (BFS) Algorithm Problem Statement Path finding is a fundamental problem in Artificial Intelligence where an intelligent agent must find a valid path from a starting position to a goal position while avoiding obstacles. In this practical, a maze is represented as a two-dimensional grid, and the Breadth-First Search (BFS) algorithm is https://madhushablogs.blogspot.com/2026/07/Path-Finding-in-a-Maze-Using-Breadth-First-Search-BFS-Algorithm .htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-5873920315390810530Wed, 15 Jul 2026 05:10:40 +00002026-07-15T10:45:17.234+05:30 From Single-Layer Perceptron to Multi-Layer Perceptron: Solving Linear and Non-Linear Problems Using Neural NetworksIntroductionArtificial Neural Networks (ANNs) are inspired by the structure and functioning of the human brain. At the core of every ANN lies a simple computational unit called the Perceptron. A perceptron receives inputs, processes them mathematically using weights and bias, https://madhushablogs.blogspot.com/2026/07/Linear-and-Non-Linear-Problems-Using-Neural-Networks.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-7884544151342459529Tue, 14 Jul 2026 04:58:01 +00002026-07-15T15:07:18.054+05:30AIartificial intelligenceData ScienceDeep LearningMachine LearningNLP Artificial Neural Networks (ANN) Understanding the Foundation of Deep Learning Artificial Intelligence (AI) has transformed the way machines solve real-world problems. Applications such as ChatGPT, facial recognition, speech assistants, self-driving cars, medical diagnosis, recommendation systems, and fraud detection are all powered by Deep Learning. At the heart of Deep Learning lies one https://madhushablogs.blogspot.com/2026/07/Understanding-the-Foundation-of-Deep-Learning.htmlnoreply@blogger.com (Dr.Manisha More)0tag:blogger.com,1999:blog-331977333533137262.post-8354803294035600503Mon, 13 Jul 2026 03:58:06 +00002026-07-13T09:28:06.128+05:30AIartificial intelligenceData ScienceMachine LearningNLP Search and Reasoning in Artificial Intelligence What is Search? Definition Search is the process of finding the best or correct solution from multiple possible solutions. Simple Examples Finding a file on your laptop Finding the shortest route in Google Maps Searching a contact on your phone AI finding the best chess move Real-Life Example Suppose you lost your keys. You https://madhushablogs.blogspot.com/2026/07/Search-and-Reasoning-in-AI.htmlnoreply@blogger.com (Dr.Manisha More)0