v2

Training Models: Local vs. Cloud

Time Investment in Model Training

• Training a model on a local computer can take anywhere from 12 to 48 hours, while using cloud resources can reduce this time to just one hour due to the availability of more computational power.

• It's important to consider that cloud development incurs higher costs, necessitating careful management of resources.

Cost Management Strategies

• The discussion highlights the need for variation pipelines to avoid escalating costs associated with cloud computing.

Ethical Considerations in Data Analytics

Ethical Dilemmas in Machine Learning

• A question arises about potential ethical conflicts when using machine learning algorithms based on customer purchasing behavior, particularly regarding privacy concerns.

Importance of Professional Ethics

• Emphasizes the necessity of handling sensitive client information ethically, especially when working with analytical models that require extensive data.

Confidentiality Agreements and Data Classification

Handling Sensitive Information

• When developing analytical models, confidentiality agreements are crucial as they govern access to privileged information about clients.

Classifying Data for Model Development

• The classification of data is essential; it involves determining which variables are necessary for achieving the model's objectives while ensuring ethical standards are maintained.

Practical Applications of Data Analysis

Case Study Request

• An audience member requests an example where data analysis improved efficiency within a company.

Recent Developments in Analytical Models

• Discussion includes recent work on developing an analytical model related to QR code payments, indicating ongoing efforts to enhance banking processes through technology.