Related Courses:Data Visualization, Data Mining, Deep learning, Neural Network,Big Data Analytics
Related Courses: Project Management, Algorithm, Manufacturing Engineering, Business Analysis
Related Courses: Data Structure, Financial, Investments, Financial Derivatives
• Analyze the main selling product changes after the Premium cliff on early July
• Establish a machine learning model by python and obtain the analytical base table from daily report forms to predict high potential existing customers for cooperated agents
• Double the cooperated agents' sales turnover rate than the agents who didn't work with us
• Created 1700 interaction points by interactive activities of six sigma tools (DMAIC, 5S, etc.)
• Improve employees’ efficiency by established database for Import Customs Charge Department
Python (Numpy, Pandas, Scikit-Learn, TensorFlow, Keras) , R, C++, SQL, Spark, SAS, Tableau, Hadoop, AWS
• Built up a KRR model to predict stock price by other field relevant stock prices with 0.8% RMSE. Adjust the model by top 10 error cases.
• Construct a 70% accurate rate classifier implement by Logistics Regression, Natural Language Processing to identify 2000 corpuses.
• Apply KNN, SVM, PCA to identify tons of digits with 81.28% accurate rate
• Formulate and visualize a marketing strategy by utilize EDA, K-Means and Hierarchical Clustering on customers' information to target market advertisement.
• Forecast stock price with 1.3% RMSE by using Auto Encoder technique and MLP predictor. Seek out the importance between each input and improve the algorithm.
• Improved about 20% efficiency of Chunghwa Telecom company by developing the dual problem of Data Envelopment Analysis; found the potential power for improving efficiency by dual, surplus and slack variables