A job recommender system was developed involving extensive data analysis and visualization. Clustering techniques were implemented to group job preferences and skills, enhancing recommendation accuracy. Four algorithms were applied to refine recommendations, leveraging data insights to match candidates with suitable roles effectively.

• Pandas - working with dataset
• NLTK - preprocessing the data
• SK Learn - Implement ML algorithms
• Word Cloud - Data Analysis
• Seaborn - Visualization
• Matplotlib - Visualization

• Remove unwanted columns
• Remove Duplicates
• Drop empty columns
• Data mining extract feature from our text using TF-IDF

• Top 5 Demand Jobs in IT

• Most Used Skill in IT - Word Cloud

• k-means Algorithm
• Classify the clustering by giving names

• Logistic Regression
• KNN
• Decision Tree
• Support Vector Machine
• Accuracy comparison between 4 algorithms

• Cosine Similarity
• Euclidean Distance

• Cosine Similarity
• SVM