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R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.
Why are statistical programming languages important to data scientists? What are some advantages and disadvantages the R programming language has over the other main statistical programming languages (i.e. Python, SAS, SQL)?
When replying to a classmate, offer your opinion on what they posted comparing the R programming language to the other statistical programming languages. Using at least 3 – 5 sentences, explain why you agreed or disagreed with their evaluation of the different statistical programming languages.
Discussion 2 (Chapter 2): Discuss the process that generates the power of AI and discuss the differences between machine learning and deep learning.
Note: The first post should be made by Wednesday 11:59 p.m.,
Chapter 2 – Discussion question #1 &
Discuss the difficulties in measuring the intelligence of
Exercise question #4 &4. In 2017, McKinsey & Company created a five-part video
titled “Ask the AI Experts: What Advice Would You Give
to Executives About AI?” View the video and summarize
the advice given to the major issues discussed. (Note:
This is a class project.)
Exercise question #5 &5. Watch the McKinsey & Company video (3:06
min.) on today’s drivers of AI at youtube.com/
watch?v=yv0IG1D-OdU and identify the major AI
drivers. Write a report.
Exercise question 15 (limit to one page of analysis for question 15)15. Explore the AI-related products and services of Nuance
Inc. (nuance.com). Explore the Dragon voice recogni