English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 0h 36m | 79 MB
Demand is increasing for data-driven decision-making and the rapid integration of Python in Excel and ML across business sectors. In this course, Finance Transformation Senior Manager Christian Martinez offers timely training that empowers you to efficiently leverage vast amounts of data for competitive advantage, aligning with current market needs.
Table of Contents
Introduction
1 Introduction
2 What you should know
Recap of Python, ML, and Data Cleaning
3 Recap of Python
4 Recap of machine learning
5 Data cleaning and preparation
6 Challenge How would you solve this problem with ML
7 Solution How would you solve this problem with ML
Applied Machine Learning for Finance and Business
8 Introduction to machine learning concepts
9 Building regression models in Excel
10 Classification models for business data
11 Challenge Build a regression model
12 Solution Build a regression model
Practical Applications of Machine Learning in Business and Finance
13 Predictive analytics for financial forecasting
14 Automated decision-making processes
15 Real-time data processing and analysis
16 Challenge Create a financial forecast
17 Solution Create a financial forecast
Advanced Analytical Techniques with Python Libraries
18 Data manipulation with pandas
19 Numerical analysis with NumPy
20 Machine learning with scikit-learn
Machine Learning Algorithms for Business and Finance
21 Linear regression for business insights
22 Random forests for predictive modelling
23 Clustering techniques for market segmentation
Conclusion
24 Next steps
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