knime-academy-datascience
🤟 Cevi Herdian (Knime Academic Alliance Partner) -> itsmecevi.github.io
📉 KNIME Technical Spesifications
📒 KNIME Changelog
🔮 Duration: 15 hours
Warming up
- Data Access
- ETL
- Data Manipulation & Visuallization:
- Intro to Data Manipulation in KNIME
- Rule Engine
- String Manipulation
- String Replacer
- String Splitting and Column Combining
- Column Resorter
- Type Conversion
- Database Operations
- Scatterplot
- Color Manager
- Line Plot
- Parallel Coordinate Plot
- Bar Charts
- Machine Learning:
- Introduction to Decision Tree
- Buildung Decision Tree
- Decision Tree Workflow
- Intro to K-means Clustering
- K-means Clustering in KNIME
Practicing Data Science with KNIME
- Web & Social Media:
- Document Classification: Spam vs Ham
- Topic Detection: What is it all about?
- Sentiment Analysis: What is with the tone?
- Find the influencers
- Sentiment & Influencers
- Customer Intelligence:
- Churn Prediction
- Customer Segmentation
- Retail and Supply Chain
- Market Basket Analysis with the Apriori Algorithm
- Movie Recommendations with Spark Collaborative Filtering
-
Banking and Insurance: Credit Risk Assessment
-
Web Analytics: Click Stream Analysis
- IoT:
- Bike Restocking Alert with Minimum Set of Input Features
- Taxi Demand Prediction using Random Forest on Spark
- Anomaly Detection
- Cybersecurity:
- Fraud detection
- Fraud detection using a neural auto-encoder
- Text Generation:
- Neural Machine Translation with RNN
- Product Naming with Deep Learning for Marketers and Retailers-Keras Inspired