Answer / Rakhi Verma

The Netflix Prize was a public competition held between 2006 and 2009 to develop a movie recommendation algorithm that could improve upon Netflix's existing system by at least 10%. To approach this competition, teams would focus on developing sophisticated collaborative filtering algorithms based on user ratings data. Techniques used included matrix factorization methods such as singular value decomposition (SVD), alternating least squares (ALS) optimization, and latent Dirichlet allocation (LDA). Teams also experimented with hybrid approaches that combined content-based and collaborative filtering techniques.

You are given a data set. The data set has missing values which spread along 1 standard deviation from the median. What percentage of data would remain unaffected? Why ?

1 Answers  

---

Tell me how is knn different from k-means clustering?

1 Answers  

---

Name a few libraries in Python used for Data Analysis and Scientific Computations?

1 Answers  

---

Tell me what is a recommendation system?

1 Answers  

---

Why is python so popular in machine learning?

1 Answers  

---

What are the most common types of machine learning task?

1 Answers  

---

What are the best python libraries used in machine learning?

1 Answers  

---

Explain the Inductive Learning in Machine Learning?

1 Answers  

---

What is the best language to learn machine learning?

1 Answers  

---

Is machine learning a good career?

1 Answers  

---

Explain the Algorithm Technique of Transduction in Machine Learning?

1 Answers  

---

Which language is better for machine learning r or python?

1 Answers  

---