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I am an Electrical Engineer (5-year experience). I transitioned from an electrical engineer to a data scientist.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
kaggle-competitions
October 22, 2020 – January 14, 2021
kaggle-competitions — GitHub repository
View Projectweb-Scrabing
October 19, 2020 – October 19, 2020
Web scraping, web harvesting, or web data extraction is data scraping used for extracting data from websites.
View ProjectTime-Series
October 19, 2020 – October 19, 2020
It is the chronological arrangement of data with Equal interval and time.
View ProjectClustering
October 19, 2020 – October 19, 2020
The aim is to segregate groups with similar traits and assign them into clusters.
View ProjectDecision-Tree-and-Random-Forest
October 19, 2020 – October 19, 2020
Decision tree is a supervised machine learning algorithm mainly used for the Regression and Classification. This graphical representation which classifies the data is called as the Decision Tree.
View ProjectNaive-Bayes-KNN
October 19, 2020 – October 19, 2020
basic code of Naive Bayes and K-Nearest Neighbour
View Projectlogistic-regression
October 19, 2020 – October 19, 2020
to solve/predict the categorical (binary) output through logistic regression( sklearn library)
View Projectlinear-regression
October 19, 2020 – October 19, 2020
linear regression is a linear approach to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables).
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and focused on foundational machine learning concepts, indicating a strong individual learning drive. However, the lack of team projects or diverse application areas makes it difficult to assess cultural fit in a collaborative, production-oriented environment. The projects align with the technical domain of a Data Scientist role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are very brief, limiting insight into their communication style or problem-solving approach beyond technical implementation.