Great talk. Some parts of R and Python are very similar such as read_csv() in the tidyverse and pandas where both produce a data frame. But, in Python the adoption of the data frame is limited and as one progresses in machine learning one is dealing with numpy arrays and tensors rather than data frames. Good example in "cost" vs. "c" parameters. I tend to trust R more but like Python's spirit of experimentation.
Great talk. Some parts of R and Python are very similar such as read_csv() in the tidyverse and pandas where both produce a data frame. But, in Python the adoption of the data frame is limited and as one progresses in machine learning one is dealing with numpy arrays and tensors rather than data frames. Good example in "cost" vs. "c" parameters. I tend to trust R more but like Python's spirit of experimentation.