Blockchain Data Analytics For Dummies. Michael G. Solomon
Читать онлайн книгу.Part 2: Fetching Blockchain Chain Chapter 6: Parsing Blockchain Data and Building the Analysis Dataset Comparing On-Chain and External Analysis Options Integrating External Data Identifying Features Building an Analysis Dataset Chapter 7: Building Basic Blockchain Analysis Models Identifying Related Data Making Predictions of Future Outcomes Analyzing Time-Series Data Chapter 8: Leveraging Advanced Blockchain Analysis Models Identifying Participation Incentive Mechanisms Managing Deployment and Maintenance Costs Collaborating to Create Better Models
5 Part 3: Analyzing and Visualizing Blockchain Analysis Data Chapter 9: Identifying Clustered and Related Data Analyzing Data Clustering Using Popular Models Implementing Blockchain Data Clustering Algorithms in Python Discovering Association Rules in Data Determining When to Use Clustering and Association Rules Chapter 10: Classifying Blockchain Data Analyzing Data Classification Using Popular Models Implementing Blockchain Classification Algorithms in Python Determining When Classification Fits Your Analytics Needs Chapter 11: Predicting the Future with Regression Analyzing Predictions and Relationships Using Popular Models Implementing Regression Algorithms in Python Determining When Regression Fits Your Analytics Needs Chapter 12: Analyzing Blockchain Data over Time Analyzing Time Series Data Using Popular Models Implementing Time Series Algorithms in Python Determining When Time Series Fits Your Analytics Needs
6 Part 4: Implementing Blockchain Analysis Models Chapter 13: Writing Models from Scratch Interacting with Blockchains Connecting to a Blockchain Examining Blockchain Client Languages and Approaches Chapter 14: Calling on Existing Frameworks Benefitting from Standardization Focusing on Analytics, Not Utilities Leveraging the Efforts of Others Chapter 15: Using Third-Party Toolsets and Frameworks Surveying Toolsets and Frameworks Comparing Toolsets and Frameworks Chapter 16: Putting It All Together Assessing Your Analytics Needs Choosing the Best Fit Managing the Blockchain Project
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Part 5: The Part of Tens
Chapter 17: Ten Tools for Developing Blockchain Analytics Models
Developing Analytics Models with Anaconda
Writing Code in Visual Studio Code
Prototyping Analytics Models with Jupyter
Developing Models in the R Language with RStudio
Interacting with Blockchain Data with web3.py
Extract Blockchain Data to a Database
Accessing Ethereum Networks at Scale with Infura
Analyzing Very Large Datasets in Python with Vaex
Examining Blockchain Data
Preserving Privacy in Blockchain Analytics with MADANA
Chapter 18: Ten Tips for Visualizing Data
Checking the Landscape around You
Leveraging the Community
Making Friends with Network Visualizations
Recognizing Subjectivity
Using Scale, Text, and the Information You Need
Considering Frequent Updates for Volatile Blockchain Data
Getting Ready for Big Data
Protecting Privacy
Telling Your Story