INTRODUCTION – The Different Types of Machine Learning
Understanding in Machine Learning: Here is a broader vision that one goes through initially with participant in getting through essential concepts to know its weightage into the broad field of data science. The initial part of the course would explore basic principles into the backbone of machine learning exposing the good ground for any in-depth exploration into the diverse applications.
Covers all the available dimensions of machine learning into a particular area of concentration such as supervised learning, unsupervised, reinforcement learning, and deep learning. These four types will help illuminate every participant’s grasp into real application and then weave the tapestry of complication for which understanding can bring the work from consideration to reality.
Learning Goals:
- Identify the most common online resources available in the data science field for machine learning.
- Explore Python Packages associated with machine learning, use these functions and understand their main differences.
- Identify the questions to be asked at every stage of the PACE Framework to prevent and detect unfair or unethical models.
- Understand two approaches to recommendation systems.
- Further, Continuous and Categorical variable types, and each form of machine learning are reviewed with examples.
- Identify popular and commonly used Integrated Development Environments (IDEs), resources, and libraries in Machine Learning.
- Know the significant Characteristics of the three Types of Machine Learning: Supervised learning, Unsupervised learning, and Reinforcement learning.
PRACTICE QUIZ: TEST YOUR KNOWLEDGE: INTRODUCTION TO MACHINE LEARNING
1. Fill in the blank: Machine learning involves using algorithms and _____ to teach computer systems to analyze and discover patterns in data.
- dynamic reports
- statistical models (CORRECT)
- decision-support systems
- computer software
Correct: Machine Learning is an application for the use of algorithms and statistical models to enable computer systems to analyze and find patterns in data and make decisions or predictions without being explicitly programmed.
2. A data professional using an unsupervised machine learning technique will ask a model to provide information based on a specified outcome.
- True
- False (CORRECT)
Correct: The data expert using an unsupervised machine learning technique will supply data to the model without specifying what kind of outcome they wish to achieve, allowing it to detect patterns, groupings or underlying structures for itself.
3. Which approach to machine learning involves rewarding or punishing a computer’s behaviors?
- Reinforcement learning (CORRECT)
- Supervised machine learning
- Deep learning
- Artificial intelligence
Correct: When actions taken by a computer result in positive or negative outcomes, it may be considered reinforcement learning. Consequently, it alters its policy from time to time in order to maximize rewards and/or minimize punishments, gradually improving its decision-making process with respect to the rewards given.
PRACTICE QUIZ: TEST YOUR KNOWLEDGE: CATEGORICAL VERSUS CONTINUOUS DATA TYPES AND MODELS
1. The weight of a surfboard is a continuous variable, whereas the number of surfboards currently at Bondi Beach is a discrete variable.
- True (CORRECT)
- False
Correct: Surfboard weight is a continuous variable because it can range from infinite values within a specific interval, such as in kilograms, and measured closer and closer. The number of surfboards at Bondi Beach is a discrete variable because it is countable, and each surfboard is a separate entity.
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2. A data professional is working on a project that involves labeling thousands of books by their various book genres. What type of variable should they use when working with this dataset?
- Quantitative
- Categorical (CORRECT)
- Continuous
- Discrete
Correct: Variables of category because categorical variables are finite in amount of groups or categories. These variables serve to categorize into definable categories, such as types, labels, or classifications, without any latent numerical order.
PRACTICE QUIZ: TEST YOUR KNOWLEDGE: MACHINE LEARNING IN EVERYDAY LIFE
1. What term describes the subclass of machine learning algorithms that offers relevant suggestions to users?
- Sensor techniques
- Suggestion maps
- Recommendation systems (CORRECT)
- Data models
Correct: Recommendation systems are a small category of machine learning algorithms that recommend to a user based on their preferences, behaviors, or historical data. Trying to make the experience more personal by estimating what items, products, or content one may like, as well as by personalization.
2. Content-based systems are very effective at making recommendations across content types.
- Jira (CORRECT)
- Evernote
- Excel
- Cameras
Including Jira among other ticketing systems, it forms such an extensive cycle that documentation and tracking of incidents are done well. These systems facilitate efficient logging, managing, and resolution processes, bringing transparency and accountability to these events from initial identification all the way through final resolution.
3. Fill in the blank: When several users actively like or dislike content by rating it or giving it a review, this enables _____ filtering.
- Collaborative (CORRECT)
- preferential
- crowdsourced
- merit-based
Correct: Another way is when multiple users are actively rating or reviewing such content by liking or disliking it. Then, it becomes possible to implement collaborative filtering. A recommendation system based on collaborative filtering compares users according to joint preferences or behavior and then recommends new content that other similar users have liked. In this way, that easy recommendation is based on the taste of similar users.
PRACTICE QUIZ: TEST YOUR KNOWLEDGE: ETHICS IN MACHINE LEARNING
1. In recommendation systems, what term describes the phenomenon of more well-known items being recommended too frequently?
- Non-objectivity
- Popularity bias (CORRECT)
- Trend partiality
- Fame factor
Correct: Popular bias is the inclination of recommendation systems that very often tend to suggest well-known popular items rather than that which is not so popular but items that they could have been equally attractive for the users. So, this curtails the diversification of recommendation and can lead to poor discovery of really interesting gems.
2. A data professional has just begun considering the intended purpose of a model and how harmful or significant its effects could be. Which PACE stage of model development does this scenario describe?
- Construct
- Analyze
- Execute
- Plan (CORRECT)
Correct: In this situation, the “planning” phase of model development is described. Some of those questions include how model predictions will be used, who will be affected by the outcomes of the model, and how personal information will be treated. This helps to link the model with ethics, privacy, and purposes.
PRACTICE QUIZ: TEST YOUR KNOWLEDGE: UTILIZE THE PYTHON TOOLBELT FOR MACHINE LEARNING
1. What is the term for a software application that includes an interface for writing, running, and testing a piece of code?
- HTML
- CSV
- VIF
- IDE (CORRECT)
2. Code completion automatically finishes what a data professional is typing based on the functions and variables that are present in their code.
- True (CORRECT)
- False
Correct: Code completion is the great feature where you can get automated suggestions and completing the code as a data professional types based on the functions, variables, and syntax in their code. This increases coding efficiency, decreases errors, and provides in-context suggestions that make writing and debugging code much easier.
3. What types of packages are used to load, structure, and prepare a dataset for further analysis?
- Visualization
- Operational (CORRECT)
- Machine learning
- Processing
Correct: Operational packages will read, organize, and preprocess datasets for further analysis. Some of the usual tasks that these packages perform include cleaning, transforming, and organizing the data so that it is in usable form for analysis or modeling.
PRACTICE QUIZ: TEST YOUR KNOWLEDGE: MACHINE LEARNING RESOURCES FOR DATA PROFESSIONALS
1. Fill in the blank: Documentation is a _____ written by developers that includes specific information about various functions and features of a package.
- Workbook
- code
- guide (CORRECT)
- checklist
Correct: Developers create a documentation which serves as a guiding piece for users. It contains vital details on the various functions, features, and usage of a particular package. A typical document does include description, some examples, and instruction on effectively using that package, thereby enabling the user to know its features and usage in their project.
2. If a data professional requires guidance regarding a particular piece of hardware, which team should they reach out to?
- Information technology (CORRECT)
- Product management
- Marketing
- Business intelligence
Correct: When a data professional searches for assistance regarding any specific type of hardware, he should contact IT. The role of IT personnel is to manage hardware and troubleshoot issues and to ensure that every piece of equipment operates appropriately in meeting the requirements of the data professional.
QUIZ: MODULE 1 CHALLENGE
1. Which of the following statements correctly describe supervised and unsupervised machine learning? Select all that apply.
- Unsupervised machine learning uses labeled datasets to train algorithms to classify or predict outcomes.
- Supervised machine learning uses labeled datasets to train algorithms to classify or predict outcomes. (CORRECT)
- In unsupervised machine learning, data professionals ask the model to give them information without telling the model what the answer should be. (CORRECT)
- Unsupervised machine learning involves data professionals asking a model to give them information without specifying a desired outcome. (CORRECT)
2. Fill in the blank: The terms machine learning and _____ both refer to training a computer to detect patterns in data without being explicitly programmed to do so.
- Coding
- artificial intelligence (CORRECT)
- reinforcement learning
- quality assurance
3. An analytics team at a college works on a task involving categorical variables. Which of the following variables might be part of the project dataset? Select all that apply.
- Number of books in a classroom
- Languages spoken at the college (CORRECT)
- Student nationalities (CORRECT)
- Teacher subject area expertise (CORRECT)
4. Which of the following statements accurately describes content-based filtering? Select all that apply.
- Content-based filtering effectively makes recommendations across content types.
- Content-based filtering does not require information from other users to work properly. (CORRECT)
- Content-based filtering properties often have to be selected and mapped manually. (CORRECT)
- Content-based filtering recommends more of what a user likes. (CORRECT)
5. Fill in the blank: A key benefit of collaborative filtering is that it finds hidden _____ in the data.
- duplicates
- correlations (CORRECT)
- contradictions
- errors
6. A data professional is considering whether the data they are using to build a model is well-sourced. Which PACE stage does this scenario describe?
- Plan
- Analyze (CORRECT)
- Construct
- Execute
7. Which of the following statements accurately describe Python notebooks and scripts? Select all that apply.
- Python scripts are useful for pairing code with human-readable descriptions and outputs.
- Python notebooks are executed by a computer without the need for human supervision.
- Data professionals often alternate between Python notebooks and scripts. (CORRECT)
- Data professionals can use both Python notebooks and scripts to execute code. (CORRECT)
8. Fill in the blank: The data visualization package _____ is designed primarily for statistical visualization.
- Tableau
- Plotly
- Matplotlib
- Seaborn (CORRECT)
9. Fill in the blank: In a typical business, a data professional is most likely to request assistance from the _____ department to obtain preliminary information about a dataset.
- Sales
- information technology
- business intelligence (CORRECT)
- marketing
10. A data analytics team at a household goods manufacturer works on a task involving discrete variables. Which of the following variables might be part of the project dataset? Select all that apply.
- Type of most popular toaster
- Total days a sale lasts in March (CORRECT)
- Number of appliances for sale at a retail store (CORRECT)
- Amount of people in a household (CORRECT)
11. Which of the following statements accurately describe content-based filtering? Select all that apply.
- Content-based filtering properties never have to be selected and mapped manually.
- Content-based filtering does not require information from other users to work properly. (CORRECT)
- Content-based filtering is ineffective at making recommendations across content types. (CORRECT)
- Content-based filtering can go beyond comparing items to recommending other things that match a user’s preferences. (CORRECT)
12. A data professional is considering whether the data they are using to build a model is appropriate. Which PACE stage does this scenario describe?
- Construct
- Execute
- Analyze (CORRECT)
- Plan
13. What are some advantages of Python notebooks? Select all that apply.
- They automatically choose the best machine learning model to use for a data project.
- They are useful for pairing code with human-readable descriptions and outputs. (CORRECT)
- Noncode elements can be embedded directly into the file. (CORRECT)
- They offer functional advantages, such as the ability to export PDF files. (CORRECT)
14. Fill in the blank: A data professional may request assistance from the _____ department to find out what hardware and software are available for a data project.
- sales
- business intelligence
- marketing
- information technology (CORRECT)
15. Fill in the blank: In the process of _____, policies will change depending on whether a reward or punishment is received.
- quality assurance
- artificial intelligence
- deep learning
- reinforcement learning (CORRECT)
16. A data professional at a construction company works on a task involving continuous variables. Which of the following variables might be part of the project dataset? Select all that apply.
- The number of pallets on a truck
- The age of a building (CORRECT)
- The height of a skyscraper (CORRECT)
- The weight of a concrete block (CORRECT)
17. Fill in the blank: One benefit of collaborative filtering is that it can effectively _____ across content types.
- make recommendations (CORRECT)
- produce metadata
- eliminate outliers
- visualize data
18. Which of the following applications would be well-suited to the use of Python scripts? Select all that apply.
- A task pairs code with human-readable descriptions.
- A task that requires a human-readable output (CORRECT)
- A program that incorporates several files (CORRECT)
- A program that contains errors in need of debugging (CORRECT)
19. Fill in the blank: The data visualization package _____ is effective when creating presentations, such as designing a data visualization for an interactive dashboard.
- Matplotlib
- HTML
- Tableau
- Plotly (CORRECT)
20. Fill in the blank: A data professional working on an email campaign may request assistance from the _____ department to understand the purpose of their data work and confirm they are working toward a clear target.
- business intelligence
- information technology
- finance
- marketing (CORRECT)
21. Which of the following statements correctly describe supervised and unsupervised machine learning? Select all that apply.
- Supervised machine learning uses algorithms to analyze and cluster unlabeled datasets.
- In unsupervised machine learning, data professionals ask the model to give them information without telling the model what the answer should be. (CORRECT)
- Supervised machine learning uses labeled datasets to train algorithms to classify or predict outcomes. (CORRECT)
- Data professionals use supervised machine learning for prediction. (CORRECT)
22. Fill in the blank: Matplotlib is a type of _____, which enables data professionals to create plots and graphs for data projects.
- data visualization package (CORRECT)
- machine learning package
- operational package
- mathematical package
23. Fill in the blank: The process of _____ involves models made of layers of interconnected nodes. Each layer receives signals from its preceding layer, and nodes that are activated pass transformed signals to another layer or a final output.
- deep learning (CORRECT)
- reinforcement learning
- artificial intelligence
- quality assurance
24. Fill in the blank: One drawback of collaborative filtering is that the data has a lot of _____ values.
- Missing (CORRECT)
- inaccurate
- conflicting
- redundant
25. Fill in the blank: Supervised machine learning uses labeled datasets to train _____ to classify or predict outcomes
- Clusters
- algorithms (CORRECT)
- dashboards
- networks
Correct: Supervised machine learning training is the process of giving data to an algorithm to enable it to classify information and/or predict outputs using labeled datasets. Data experts apply methods of supervised learning to such activities as estimating future values and classifying information into predefined classifications based on the existing training data.
26. What type of variables would a data professional use to classify types of homes, such as apartment, single-family, or townhouse?
- Categorical (CORRECT)
- Numeric
- Continuous
- Discrete
Correct: When they have to classify various house types, the data professionals use categorical variables to carry out the task as these represent only a finite number of different categories and groups, for instance, “apartment,” “detached house,” and “townhouse.” The event is pertinent to organizing the data but would consider it under the categorical count as there is nothing of numeric order in it.
27. Fill in the blank: Content-based filtering is a recommendation system in which the recommendations are made based on _____ of the attributes of the content.
- improvements
- comparisons (CORRECT)
- differentiations
- segmentations
Correct: The content-based filtering recommendation system makes a comparison on the basis of the attributes or characteristics of the content itself. It examines the list of features or descriptors associated with a piece of content and compares those descriptors to items having similar feature descriptors to recommend items that share similar characteristics. Such a method is especially useful when the system should suggest items similar to some of the already liked items by the user.
28. Fill in the blank: An integrated _____ environment, or IDE, is a software application that has an interface for writing, running, and testing a piece of code.
- design
- development (CORRECT)
- dynamic
- data
Correct: An integrated development environment (IDE) is used, which offers a holistic view of the complete interface for writing, running, and testing codes. It may include code editors, debuggers, compilers, and other tools that contribute in making the programming process-an efficient experience.
CONCLUSION – The Different Types of Machine Learning
Ultimately, this comprehensive overview of machine learning gives users a winning experience in understanding the core principles and diverse usages in data science. It opens the doors through which they can discover how supervised, unsupervised, reinforcement, and deep learning might solve problems, derive behavior patterns from data, and how such methodologies help solve issues.
As participants close this section of study, they acquire the capacity to apply pertinent machine learning algorithms to real-world circumstances while empowering and collapsing barriers to readiness for increased customization in data science over the years. This becomes the groundwork for any participant interested in effective application with influence in the discipline.