Project 1 - Analyzing the Education trends in Tamilnadu

https://drive.google.com/drive/folders/1CcAyLkhpRG-Kj8XZUY4wKJCC8ThcFwtz?usp=drive_link

Project as attached below

Look at the below notebook

Look at the below notebook

Refer the below file

Please refer the below ipy notebook

https://public.tableau.com/app/profile/shraddha.seshadri7958/viz/LiteracyrateinTamilNadu_16750066578870/Totalpopulation?publish=yes  

The link to the project is https://public.tableau.com/app/profile/shraddha.seshadri7958/viz/WomaninSTEMfield_16747536414930/Dashboard1?publish=yes

Analysis in pbix ppt has details

Analysis is in powerbi file Rest in powerpoint

2.Import all .csv files into MySQL

1 and 2) 3) 4) 5) 6) 7) 8) 9) 12) 10) 11) 12) 13) 14) 15) 16) 17) 18) 19) 20)  

KMeans Clustering of the dataset was performed and scatter plots were created. Hierarchical Clustering was performed and scatter plots were created. In both the clustering method the optimum number of clusters were found to be 3. The Clusters form in both the algorithms were exactly the same.  

Below file has answer to the above project

1)How does similarity is calculated if data is categorical in nature Ans 1) Different similarity calculation methods are listed below: *Source: Shirkhorshidi AS, Aghabozorgi S, Wah TY (2015). A Comparison Study on Similarity and Dissimilarity Measures in Clustering Continuous Data.

1)What is a Neural Network? Ans 1) A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural networks, composed of artificial neurons or nodes.Thus, a neural network is either a biological neural networks, made up of biological neurons, or an artificial neural…

1)What are the pros and cons of knn Advantages of KNN1. No Training Period: KNN is called Lazy Learner (Instance based learning). It does not learn anything in the training period. It does not derive any discriminative function from the training data. In other words, there is no training period for…

Pros and cons of SVM Advantages:-SVM works relatively well when there is a clear margin of separation between classes.-SVM is more effective in high dimensional spaces.-SVM is effective in cases where the number of dimensions is greater than the number of samples.-SVM is relatively memory efficientDisadvantages:-SVM algorithm…

2)Difference between L1 & L2 Gradient descent method Ans2) Mean Absolute Error, L1-(MAE) is another loss function used for regression models. MAE is the sum of absolute differences between our target and predicted variables. So it measures the average magnitude of errors in a set of predictions, without considering…

2)What is the significance of expected value when simple mean (Sum of all observations/number of observations) is already in place Ans2) The applicablity of simple mean and expected value are dependent on the nature of the case study. In smaller case studies where the random variable outcomes can be measured as frequency…

Why there is a difference in the formula of variance for population and sample Population variance we mainly consider real time data and we divide the value with the total number of elements present in the data . When we consider elements like height, blood pressure of a number of people it is physically possible to compute…

All solved in sheet