Does Machine Learning Require Coding
Programming is a part of Machine Learning. It is important to know programming languages such as Python.
Stay tuned to this page for more such information on interview questions and career assistance. You can check our other blogs about Machine Learning for more information.
You can also take up the PGP Artificial Intelligence and Machine Learning Course offered by Great Learning in collaboration with UT Austin. The course offers online learning with mentorship and provides career assistance as well. The curriculum has been designed by faculty from Great Lakes and The University of Texas at Austin-McCombs and helps you power ahead your career.
Outline The Difference Between Disinfection And Sterilization
In this section, the interviewer wants to know if you can differentiate between some important terms used in the medical technology field. This also tests your abilities to handle various medical tests with attention to detail.
Example:”When referring to sterilization, it’s a process where medical technologists conduct thorough cleansing of all medical equipment to eliminate all microbes. The term disinfection also refers to minimize the level of microbes below the danger level. I understand these terms and perform my responsibilities when other professionals use one of the terms addressing me regarding medical equipment.”
Do You Have Any Experience With Mishandling Chemicals In The Laboratory How Do You Address The Issue
Interviewers want to know candidates experiences in working in the laboratory.
Tip #1: Provide a genuine experience
Tip #2: Talk about how you address the issue
Sample Answer:
There was a time when some of the chemicals we were working on spilled. The chemical was considered hazardous. We quickly delegated tasks among ourselves to clean them up immediately. Wiping the spill, spraying alcohol quickly to avoid further damage. It was a shocking experience, but we managed to handle it well, and no harm was done.
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What Are Your Weaknesses
One of the most dreaded questions in a job interview is this one. Self-evaluation and honesty are required to answer this question.
Sample Answer
My worst flaw has to be that I take on too many projects at the same time. While being involved and participating in a variety of activities is enjoyable and beneficial to ones health, I have a tendency to take on too many projects and then abandon them. Ive started limiting myself to only taking on a few projects at a time so that I can commit the time needed to stay on track.
What Can You Tell Me About Blood Plasma
How to Answer
Understanding the different components of blood is essential for a blood bank lab tech. When interviewing for this type of position, the interviewer will ask questions to see how well you have processed what you have been taught. Remember, you didn’t get to an interview without knowing the necessary skills. Now is the time to show them off.
Written by Darby Faubion on November 17th, 2018
Entry Level
“Plasma is the liquid portion of blood. One of plasma’s main functions is transportation. It carries nutrients like glucose, amino acids, fats, and cholesterol, that are absorbed by the digestive tract .”
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Have You Ever Done Any Volunteer Work Or Public Education
How to Answer
While volunteering is likely not a requirement for, your willingness to volunteer or provide education regarding cancer research tells the interviewer that you are committed to being involved in any efforts possible to help create awareness. If you have not volunteered in the past, that’s OK. Ask about opportunities for employees to be involved with volunteering.
Written by Darby Faubion on November 17th, 2018
Entry Level
“I have done some volunteer work at a church camp a few summers in a row. My volunteer experience is not related to a healthcare field, but it has been something that I enjoy. It is very rewarding to see the smiles on faces of those that we give our time to.”
How Do You Handle A Patient Who Is Refusing To Cooperate For A Necessary Medical Test Or Procedure
The answer to this question is important because it shows how the medical technologist provides patient care. It also demonstrates how they work under pressure. The medical technologists communication and problem-solving skills should also be highlighted in their answer to this question. The ideal candidate will be able to handle the patients concerns and will also know when to get a supervisor.
What to look for in an answer:
- Ability to stay calm
- Willingness to explain information in a new way
- Knowledge of when to seek assistance from supervisors
Example:
I repeat the patients concern and explain the need to do the procedure or test in a new way that makes sense to them.
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What Advice Would You Give Others Who Are Considering Pursuing A Career As A Medical Laboratory Technician
How to Answer
We all have something of substance to add to the lives of others. Being willing to share your personal insight and experiences with others who may come after you is a privilege. An interviewer will often ask a question like this to see if you are approachable and willing to help others.
Written by Darby Faubion on January 22nd, 2019
Entry Level
“If I were to talk with someone considering this specialty, I would encourage them to make a plan of action, to visit universities and community colleges, to ask questions and never stop learning.”
Written by Darby Faubion on January 22nd, 2019
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Mention Some Of The Eda Techniques
Exploratory Data Analysis helps analysts to understand the data better and forms the foundation of better models.
Visualization
- Multivariate visualization
Missing Value Treatment Replace missing values with Either Mean/Median
Outlier Detection Use Boxplot to identify the distribution of Outliers, then Apply IQR to set the boundary for IQR
Transformation Based on the distribution, apply a transformation on the features
Scaling the Dataset Apply MinMax, Standard Scaler or Z Score Scaling mechanism to scale the data.
Feature Engineering Need of the domain, and SME knowledge helps Analyst find derivative fields which can fetch more information about the nature of the data
Dimensionality reduction Helps in reducing the volume of data without losing much information
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What Is The Exploding Gradient Problem While Using The Back Propagation Technique
When large error gradients accumulate and result in large changes in the neural network weights during training, it is called the exploding gradient problem. The values of weights can become so large as to overflow and result in NaN values. This makes the model unstable and the learning of the model to stall just like the vanishing gradient problem. This is one of the most commonly asked interview questions on machine learning.
Explain The Phrase Curse Of Dimensionality
The Curse of Dimensionality refers to the situation when your data has too many features.
The phrase is used to express the difficulty of using brute force or grid search to optimize a function with too many inputs.
It can also refer to several other issues like:
- If we have more features than observations, we have a risk of overfitting the model.
- When we have too many features, observations become harder to cluster. Too many dimensions cause every observation in the dataset to appear equidistant from all others and no meaningful clusters can be formed.
Dimensionality reduction techniques like PCA come to the rescue in such cases.
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What Is The Biggest Challenge That You Foresee In This Job
Interviewers want to know what challenges candidates may expect for the position.
Tip #1: State examples of challenges that may occur
Tip #2: Mention how to counter the challenge briefly
Sample Answer:
One of the challenges that I foresee in this position is the constant irregularities in our analysis. Our experiment results should be informative and accurate, but sometimes, errors are inevitable. I believe this role requires high patience and persistence.
What Does A Confirmatory Test Mean
Recruiters use some medical terms to test candidates applying for a medical technology position. You need to show the employer that you know the meaning of terms used in your workplace or related fields.
Example:”When conducting laboratory test, we use this term to refer to the second or alternative method used to test chemicals. Professionals in this field also use this term referring to the identification of metabolites and drugs in samples. I know this term and also use it when testing samples in the medical laboratories.”
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Is It Possible To Test For The Probability Of Improving Model Accuracy Without Cross
Yes, it is possible to test for the probability of improving model accuracy without cross-validation techniques. We can do so by running the ML model for say n number of iterations, recording the accuracy. Plot all the accuracies and remove the 5% of low probability values. Measure the left cut off and right cut off. With the remaining 95% confidence, we can say that the model can go as low or as high .
How Will You Know Which Machine Learning Algorithm To Choose For Your Classification Problem
While there is no fixed rule to choose an algorithm for a classification problem, you can follow these guidelines:
- If accuracy is a concern, test different algorithms and cross-validate them
- If the training dataset is small, use models that have low variance and high bias
- If the training dataset is large, use models that have high variance and little bias
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What Is The Best Way To Learn Machine Learning
Any way that suits your style of learning can be considered as the best way to learn. Different people may enjoy different methods. Some of the common ways would be through taking up basics of machine learning course for free, watching YouTube videos, reading blogs with relevant topics, read books which can help you self-learn.
What Do You Mean By Associative Rule Mining
Associative Rule Mining is one of the techniques to discover patterns in data like features which occur together and features which are correlated. It is mostly used in Market-based Analysis to find how frequently an itemset occurs in a transaction. Association rules have to satisfy minimum support and minimum confidence at the very same time. Association rule generation generally comprised of two different steps:
- A min support threshold is given to obtain all frequent item-sets in a database.
- A min confidence constraint is given to these frequent item-sets in order to form the association rules.
Support is a measure of how often the item set appears in the data set and Confidence is a measure of how often a particular rule has been found to be true.
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What Are Your Strengths
Be sure to mention qualities that would make you a good candidate for MIT, such as being hardworking or resilient. Theyre looking for students who will put in the effort and work hard to succeed.
Example Answer: I would say that some of my strengths include being able to think outside the box, being analytical, and working well under pressure, and very determined person. If I want something, Ill do whatever it takes to achieve it.
Ive developed these skills over time by taking on various challenges in life. Im always willing to learn more and take on new responsibilities. Those qualities would come in handy at MIT!
A Data Set Is Given To You And It Has Missing Values Which Spread Along 1 Standard Deviation From The Mean How Much Of The Data Would Remain Untouched
It is given that the data is spread across mean that is the data is spread across an average. So, we can presume that it is a normal distribution. In a normal distribution, about 68% of data lies in 1 standard deviation from averages like mean, mode or median. That means about 32% of the data remains uninfluenced by missing values.
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Can You Tell What Glp Is
Recruiters can involve this question in an interview to see if you understand the meaning of some abbreviations used in the medical laboratories. Outline the purpose and discuss how professionals in the field use the term.
Example:”We regularly use GLP in the laboratories, meaning good laboratory practices. It is a setting or framework where research programs are planned, recorded, performed and reported.”
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What Is Bias Variance And What Do You Mean By Bias
Both are errors in Machine Learning Algorithms. When the algorithm has limited flexibility to deduce the correct observation from the dataset, it results in bias. On the other hand, variance occurs when the model is extremely sensitive to small fluctuations.
If one adds more features while building a model, it will add more complexity and we will lose bias but gain some variance. In order to maintain the optimal amount of error, we perform a tradeoff between bias and variance based on the needs of a business.
Bias stands for the error because of the erroneous or overly simplistic assumptions in the learning algorithm . This assumption can lead to the model underfitting the data, making it hard for it to have high predictive accuracy and for you to generalize your knowledge from the training set to the test set.
Variance is also an error because of too much complexity in the learning algorithm. This can be the reason for the algorithm being highly sensitive to high degrees of variation in training data, which can lead your model to overfit the data. Carrying too much noise from the training data for your model to be very useful for your test data.
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What Are Overfitting And Underfitting Why Does The Decision Tree Algorithm Suffer Often With Overfitting Problems
Overfitting is a statistical model or machine learning algorithm that captures the datas noise. Underfitting is a model or machine learning algorithm which does not fit the data well enough and occurs if the model or algorithm shows low variance but high bias.
In decision trees, overfitting occurs when the tree is designed to fit all samples in the training data set perfectly. This results in branches with strict rules or sparse data and affects the accuracy when predicting samples that arent part of the training set.
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Has There Ever Been An Emergency Situation In Your Department And How Did You/would You React In Such A Situation
How to Answer
Depending on the situation, you will want to respond quickly and make yourself available to assist the doctor in any way you can. Be aware of the surroundings and also observe the patient. Your best response will be one where you are sensitive to the situation by listening closely to the doctor and nurses involved. There may not be anything you can do to help, but if you get in the way, you could definitely create more problems. Ask what you can do and pay attention. If you need to step aside, be respectful and understanding.
Written by Darby Faubion on January 22nd, 2019
Entry Level
“That really depends on the situation. I always try to remember to remain as calm as possible and report to my designated area as quickly as possible and follow emergency protocol.”
Written by Darby Faubion on January 22nd, 2019
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What Is Bias And Variance In A Machine Learning Model
Bias
Bias in a machine learning model occurs when the predicted values are further from the actual values. Low bias indicates a model where the prediction values are very close to the actual ones.
Underfitting: High bias can cause an algorithm to miss the relevant relations between features and target outputs.
Variance
Variance refers to the amount the target model will change when trained with different training data. For a good model, the variance should be minimized.
Overfitting: High variance can cause an algorithm to model the random noise in the training data rather than the intended outputs.
What Are Some Differences Between A Linked List And An Array
Arrays and Linked lists are both used to store linear data of similar types. However, there are a few difference between them.
| Array | |
| Elements are well-indexed, making specific element accessing easier | Elements need to be accessed in a cumulative manner |
| Operations are faster in array | Linked list takes linear time, making operations a bit slower |
| Arrays are of fixed size | Linked lists are dynamic and flexible |
| Memory is assigned during compile time in an array | Memory is allocated during execution or runtime in Linked list. |
| Elements are stored consecutively in arrays. | Elements are stored randomly in Linked list |
| Memory utilization is inefficient in the array | Memory utilization is efficient in the linked list. |
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Why Does Xgboost Perform Better Than Svm
First reason is that XGBoos is an ensemble method that uses many trees to make a decision so it gains power by repeating itself.
SVM is a linear separator, when data is not linearly separable SVM needs a Kernel to project the data into a space where it can separate it, there lies its greatest strength and weakness, by being able to project data into a high dimensional space SVM can find a linear separation for almost any data but at the same time it needs to use a Kernel and we can argue that theres not a perfect kernel for every dataset.
