Data science flash cards

Collecting, Managing, and Analyzing Data

Key steps include data collection, data cleaning and validation, data storage, and data analysis to extract insights.

Data Mining

The process of discovering patterns and relationships in large datasets to predict outcomes.

Large-Scale Data Analysis

Challenges include handling large data volumes, ensuring quality, and extracting insights quickly.

Ethical Considerations in Data Analysis

Involves data privacy, informed consent, transparency, and reducing algorithmic bias.

Benefits of Cloud Computing

Scalability, cost efficiency, flexibility, disaster recovery, and global accessibility.

Examples of Cloud Services

Include Google Drive (storage), AWS Lambda (processing), and Microsoft 365 (software on demand).

Cloud Service Models

IaaS (virtual hardware), PaaS (platform/tools for development), SaaS (fully developed software).

Artificial Intelligence in the Cloud

Enables access to AI services without local hardware, supporting tasks like image and speech recognition.

Machine Learning

Built on algorithms that learn from data to improve predictions and decisions over time.

Deep Learning

A subset of machine learning using neural networks with many layers for complex tasks.

Natural Language Processing (NLP)

AI branch that enables computers to understand and respond to human language.

Microsoft Azure Cloud Platform

Microsoft’s cloud platform offering services for compute, analytics, storage, and networking.

Azure Bot Service

A Microsoft toolset for building and managing conversational bots across channels.

Intents in Azure Bot Service

They represent user goals or what the user wants to achieve through their message.

Dialogs in Azure Bot Service

Manage multi-turn conversations, helping the bot keep track of the flow.

Triggers in Azure Bot Service

Used to activate specific actions or responses when a certain input is detected.

Recognizers in Azure Bot Service

Interpret user input to determine intents and extract key data.

Actions in Azure Bot Service

Tasks the bot performs, like sending messages or gathering user data.

Natural Language Understanding (NLU)

A part of NLP focused on interpreting the meaning and intent of input.

Utterances in Bot Development

Sample phrases a user might say to express a specific intent.

Entities in Bot Development

Important pieces of information extracted from user input (e.g., date, location).

Building Responsible Bots

Includes ensuring fairness, transparency, accessibility, and avoiding harmful responses.