How does the Actor-Critic model differ from traditional Q-learning in reinforcement learning?
- In Actor-Critic, the Actor and Critic are separate entities.
- Q-learning uses value iteration, while Actor-Critic uses policy iteration.
- Actor-Critic relies on neural networks, while Q-learning uses decision trees.
- In Q-learning, the Critic updates the policy.
The Actor-Critic model is different from traditional Q-learning as it separates the task of policy learning (Actor) from value estimation (Critic), whereas in Q-learning, these functions are often combined. This separation allows for more flexibility and efficiency in learning policies in complex environments.
A bank wants to use transaction details to determine the likelihood that a transaction is fraudulent. The outcome is either "fraudulent" or "not fraudulent." Which regression method would be ideal for this purpose?
- Decision Tree Regression
- Linear Regression
- Logistic Regression
- Polynomial Regression
Logistic Regression is the ideal choice for binary classification tasks, like fraud detection (fraudulent or not fraudulent). It models the probability of an event occurring, making it the right tool for this scenario.
Why is ethics important in machine learning applications?
- To ensure fairness and avoid bias
- To improve model accuracy
- To speed up model training
- To reduce computational cost
Ethics in machine learning is vital to ensure fairness and avoid bias, preventing discrimination against certain groups or individuals in model predictions. It's a fundamental concern in the field of AI and ML.
Policy Gradient Methods aim to optimize the ________ directly in reinforcement learning.
- Policy
- Value function
- Environment
- Reward
In reinforcement learning, Policy Gradient Methods aim to optimize the policy directly. The policy defines the agent's behavior in an environment.
How does the Git Large File Storage (LFS) handle binary files differently from standard Git?
- LFS stores binary files in a separate server
- LFS stores pointers to large files instead of the files themselves
- LFS compresses binary files before storing
- LFS converts binary files to text before storage
Git LFS doesn't store the actual binary files in the repository; instead, it stores pointers to them. This helps manage large files more efficiently without bloating the Git repository.
The command git reset ______ is used to reset the current HEAD to the specified state.
- hard
- soft
- mixed
- revert
The correct option is hard. The git reset --hard command resets the current branch and working directory to the specified commit. This option discards all changes, so use it with caution.
To prevent accidental commits of confidential data, Git can use a pre-commit ________.
- hooks
- filters
- validations
- scripts
In Git, pre-commit hooks allow you to perform actions or checks before a commit is completed. They are often used to prevent committing sensitive data, making "hooks" the correct term in this context.
How does Git track changes within a repository?
- Through file timestamps
- By creating snapshots of the changes
- Using file checksums for changes
- Tracking changes through external logs
Git tracks changes by creating snapshots of the entire repository at different points in time. Each snapshot (commit) contains a reference to the previous snapshot, forming a chain of changes.
In a collaborative environment, a developer wants to contribute to a project they don't have write access to. What Git workflow should they follow?
- Feature Branch Workflow
- Gitflow Workflow
- Forking Workflow
- Centralized Workflow
The Forking Workflow is suitable for situations where a developer wants to contribute to a project without having direct write access. They fork the repository, create a feature branch in their fork, and then submit a pull request for the changes to be merged into the main project.
Major Git successes often highlight the importance of ________ in managing large and complex repositories.
- Efficient Branching
- Proper Commit Messages
- Git Hooks
- Collaboration and Communication
Successful Git implementations often emphasize the significance of effective collaboration and communication. Managing large and complex repositories requires teams to work cohesively, follow proper branching strategies, and communicate changes effectively. This ensures that the development process remains organized and streamlined, leading to successful outcomes in major projects.