Category: Introduction to Machine Learning

If you can, answer the question below: Write your answer in the comment box. Do you mix test data with training data at all – at any time?

If you can, answer the question below: Write your answer in the comment box. What do we achieve with boosting Bagging and Stacking?

If you can, answer the question below: Write your answer in the comment box. In real-life: will you choose the best algorithm? or you can just use the most familiar algorithm to you. What are the pros and cons.

If you can, answer the question below: Write your answer in the comment box. What is MLOps?

If you can, answer the question below: Write your answer in the comment box. How do Tensorflow- PyTorch- MXNet differ from AWS SageMaker?

If you can, answer the question below: Write your answer in the comment box. What are some components and/or steps in AWS Sagemaker?

If you can, answer the question below: Write your answer in the comment box. Sagemaker build- Sagemaker Train- Sagemaker deploy: what are these?

If you can, answer the question below: Write your answer in the comment box. Do boosting Bagging and Stacking relate to only one algorithm such as Decsion tree? How or how not?

If you can, answer the question below: Write your answer in the comment box. What are some practical tools used for machine learning and related?

If you can, answer the question below: Write your answer in the comment box. What is Amazon Native AI/ML service called?

If you can, answer the question below: Write your answer in the comment box. Did you ever work with Sage Maker?

If you can, answer the question below: Write your answer in the comment box. Will you invest too much time to select the best algorithm?

If you can, answer the question below: Write your answer in the comment box. What are some core and common challenges in Machine Learning?

If you can, answer the question below: Write your answer in the comment box. Do you assume that corporate leaders always can ask interesting questions that ML can answer?

If you can, answer the question below: Write your answer in the comment box. What is Regression? When do we use Regression? Is Regression a Learning? i.e. a Machine Learning?

If you can, answer the question below: Write your answer in the comment box. What are the differences between k-nearest neighbor and k-means clustering?

If you can, answer the question below: Write your answer in the comment box. Are k-nearest neighbor and k-means clustering both supervised and/or unsupervised?

If you can, answer the question below: Write your answer in the comment box. How is the computational complexity of k-nearest neighbor and k-means clustering? Are they do once and use always solution?

If you can, answer the question below: Write your answer in the comment box. If the Data Changes i.e. new data comes what happens to k-nearest neighbor and k-means clustering?

If you can, answer the question below: Write your answer in the comment box. What is a decision tree?

If you can, answer the question below: Write your answer in the comment box. What is entropy in decision tree?

If you can, answer the question below: Write your answer in the comment box. What is the assumption of the Input in Naive Bayes?

If you can, answer the question below: Write your answer in the comment box. What is Bagging?

If you can, answer the question below: Write your answer in the comment box. What is Stacking?

If you can, answer the question below: Write your answer in the comment box. What is Naive Bayes? Why is it called Naive Bayes?

If you can, answer the question below: Write your answer in the comment box. Does Naive Bayes uses Conditonal Probability? If so how and why?

If you can, answer the question below: Write your answer in the comment box. Bias and Variance in the data and corresponding effect. Can you explain that?

If you can, answer the question below: Write your answer in the comment box. What is VC dimension?

If you can, answer the question below: Write your answer in the comment box. Bias and Variance in the prediction and corresponding effect. Can you explain that?

If you can, answer the question below: Write your answer in the comment box. What do desire in bias and variance in the prediction. Answer in terms of High and Low.

If you can, answer the question below: Write your answer in the comment box. What are some core and/or popular Machine Learning Algorithms.

If you can, answer the question below: Write your answer in the comment box. What is boosting?

If you can, answer the question below: Write your answer in the comment box. What is Semi-Supervised Machine Learning? Give some examples? When do we use semi-supervised Machine Learning? Best fit for what?

If you can, answer the question below: Write your answer in the comment box. What is Reinforcement Learning? Give some examples? When do we use Reinforcement Learning? Best fit for what?

If you can, answer the question below: Write your answer in the comment box. Can we do Reinforcement Learning without training step? If so how? Can you name any approach/algorithm if any in this regard?

If you can, answer the question below: Write your answer in the comment box. What do you mean by Exploration and Exploitation when it comes down to Reinforcement Learning?

If you can, answer the question below: Write your answer in the comment box. What are some important concepts to learn in Machine Learning?

If you can, answer the question below: Write your answer in the comment box. What is Machine Learning Anyway?

If you can, answer the question below: Write your answer in the comment box. What is the difference between Machine Learning and Artificial Intelligence?

If you can, answer the question below: Write your answer in the comment box. What are the different types of Machine Learning?

If you can, answer the question below: Write your answer in the comment box. What is Supervised Machine Learning? Give some examples? When do we use Supervised Machine Learning? Best fit for what?

If you can, answer the question below: Write your answer in the comment box. What is Unsupervised Machine Learning? Give some examples? When do we use Unsupervised Machine Learning? Best fit for what?