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Mtech Engineer Programming in python language
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
LDA-Linear-Discriminant-Analysis-for-Seed-Dataset
June 30, 2020 – June 30, 2020
LDA(Linear Discriminant Analysis) for Seed Dataset
View ProjectPCA-Principle-Component-Analysis-For-Seed-Dataset
June 30, 2020 – June 30, 2020
PCA(Principle Component Analysis) For Seed Dataset in Machine Learning
View ProjectKmeans-and-Hierarchical-clustering-for-Seed-dataset
June 30, 2020 – June 30, 2020
Kmeans and Hierarchical clustering for Seed-dataset in Machine Learning
View ProjectLDA-Linear-discriminant-Analysis-for-Wine-Dataset
June 30, 2020 – June 30, 2020
LDA(Linear discriminant Analysis) for Wine Dataset in machine learning
View ProjectLinear-discriminant-Analysis-LDA-for-Wine-Dataset
June 29, 2020 – June 29, 2020
Linear discriminant Analysis(LDA) for Wine Dataset of Machine Learning
View ProjectPCA-Principle-Component-Analysis-For-Wine-dataset
June 29, 2020 – June 29, 2020
PCA(Principle Component Analysis) For Wine dataset in ML
View ProjectKmeans-and-HCA-clustering-Visualization-for-WINE-dataset
June 29, 2020 – June 29, 2020
Kmeans and HCA clustering Visualization for WINE dataset in machine learning.
View ProjectLDA-Linear-discriminant-Analysis--clustering-visualization-for-Iris-dataset
June 29, 2020 – June 30, 2020
Linear discriminant Analysis clustering Visualization for IRIS dataset
View ProjectPCA-Iris-Clustering-Visualization
June 24, 2020 – June 29, 2020
Principle Component Analysis Clustering Visualization for Iris dataset
View ProjectFlask-program-For-Wine-Dataset
June 22, 2020 – June 29, 2020
Introducing Flask Program for wine Dataset
View ProjectCultural Fit Analysis
The candidate's projects show a strong focus on foundational machine learning concepts, which aligns with the technical aspects of a Data Scientist role. However, the lack of diverse project types, real-world problem-solving, or team-based work limits the assessment of cultural fit beyond technical alignment. The projects are repetitive in nature, primarily applying the same few algorithms to different standard datasets (Wine, Seed, Iris).
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's projects are primarily academic exercises focused on applying standard algorithms to well-known datasets, offering limited insight into collaborative work, problem-solving under pressure, or communication skills.