TKM1 Task 2

A discussion of the topic will reinforce the learning objectives of this lecture as students will research the topic and thereby enhance their learning and level of understanding. The interaction of ideas here will also be a healthy exposure to different perspective on the topic.

watch the following videos from the YouTube channel StatQuest:● Machine Learning Fundamentals: Sensitivity and Specificity● ROC and AUC, Clearly Explained!After reading and watching those videos, you should write a short essay that answers the followingquestions in your own words:● What is precision, recall, sensitivity, and specificity? How would you explain it to someone new tothe field of machine learning?● What is the precision/recall trade-off? Provide an unique example to illustrate the concept.● Explain the ROC curve and how it is used.

Lab Work 5 Objective • Understand the difference between creational, structural, and behavioral design patterns. • For given scenario student will detect what appropriate behavioral design patterns should be used. • Ability to use several design patterns for given scenario. Current Lab Learning Outcomes (LLO) By completion of the lab the students should be able to 1. Select the most appropriate design pattern for a give scenario 2. Implement any GoF creational design pattern 3. Apply structural GoF design patterns 4. Write code using GoF behaviour design patterns 5. Produce a pattern based design that maps the requirements of a given scenario using design patterns. Lab Requirements IDE, UML Tool. Lab Assessment Design class diagram and implementation for following scenario with demo: • A factory company produces three different products (Al, A2, and A3). Those products get combined after all three products completed. Use at least two behivoral design patterns to implement factory…

What image do you have of an email in your mind? An email's journey begins and ends at the same area. Keep track of your findings. Why are there disparities in the first place? Have you noticed the variations in model detail (or abstraction)?

In this course, you learned key concepts and tools used in machine learning. Obviously, this field cannot possibly be covered in one course, regardless of length or learning modality. How would you describe your ability to relate the course concepts to real-world problems? If presented with a problem or challenge, how confident are you that this course has equipped you with the skills to build an appropriate machine learning model? If a particular machine learning topic of interest has not been covered, to what extent has this course has equipped you with the ability to expand your knowledge by learning on your own?

What are some key steps in developing a machine learning model?

What evaluation methods would you employ to assess the efficacy of a machine learning model?

What is your impression of email? How do you recommend sending an electronic mail message? Take notes on your newfound knowledge. How are they different, and why do we see so many of them? How can I tell the difference between models with varying levels of complexity (or abstraction)?

What is unsupervised learning, and how are obstacles associated with it classified?

What picture do you have in your head when you think about e-mail? When a message is sent, how does it get to the person who is supposed to receive it? Make a note of all of the information you've gathered thus far. What are the differences, and why are they important to understand? Consider the degree of detail (or the level of abstraction) that various types of models possess in comparison to one another.

What conjures up in your thoughts when you think of an email? What factors into the length of time it takes to send an email from one place to another? Keep a journal to help you remember important details. Where do they diverge from one another? Do you know the level of detail (or abstractness) that each model has?

What image do you have of e-mail in your mind? When a message is sent, how is it delivered to its intended recipient? Make a note of the information you've gleaned. What are the distinctions and why are they significant? Consider the level of detail (or level of abstraction) that different kinds of models contain.

What is the difference between Supervised Learning Unsupervised Learning?

QUESTION 3 Consider your answers to parts C and E of learning project 1 where you used the logical counters of ways strategy and a systematic empirical observation strategy, respectively. What condition(s) do you think would be necessary, from the choices below, to guarantee the same outcome with each way of knowing? 1 or more answers     Applying common sense in how you throw the dice and in how you reason out the answer.     Making sure that in the systematic empirical observation, the 3 dice were fair and that the environmental conditions (e.g., flatness of the surface, humidity,temperature) were neutral in that they would not influence the throw of the dice     Vetting the person rolling the dice (or creating the software program) to make sure that they are an expert in probabilities.     Asking the right person to apply the logical counters of ways solution

What are some simple terms you might use to describe machine learning? Using simple examples is a good way to convey the concept.

How can using a model, rather than a tangible thing or circumstance, allow you to examine and explore with more accuracy?

What conjures up in your thoughts when you think of an email? What factors into the length of time it takes to send an email from one place to another? Keep a diary to jog your memory of significant events and details. Where do they diverge from one another? Do you know the level of detail (or abstractness) that each model has?

Define the phrase "learning agents" and explore how they are used in education.

How can using a model, rather than a tangible item or circumstance, allow you to examine and explore with more accuracy?

How does the addition of technology to the lesson plan compare favourably and unfavourably to the use of other methods?

Discuss how you learned (as a child) to not touch a hot plate on an oven. Give some examples or share a moment when you experienced that. Reflect on this through the idea of learning by and through tacit knowledge (silent learning or from watching someone else do something). Then describe the good and bad aspects of your learning experience. Explain how you would alter the learning process for your child (if you have one or are watching someone’s child). What adaptions from technology would you use to re-design or create a model for instruction? Do you think some products need to be redesigned to avoid the child’s bad experience? Please make sure you utilize a point from your required text and one exterior citation after experiencing the exercise.

What are the differences between supervised, unsupervised, and reinforcement learning?

Why it is important to design a learning system for Machine Learning problems. Explain the steps to design the system with a suitable example.