Machine Learning question

We need to fit a discriminative model using gradient descent. Model will be multi-class logistic regression:

p(tk = 1|x, w) exp(w[x) :-, exp(w?x) Omit bias intercept) parameters for this question. (a) (5pts) How many parameters does this model have? (b) (10pts) Write down the log-likelihood and convert it into a minimization problem over the cross-entropy loss E. Derive the gradient of E with respect to each wk, i.e., Vwk E(w). p(tk = 1|x, w) exp(w[x) :-, exp(w?x) Omit bias intercept) parameters for this question. (a) (5pts) How many parameters does this model have? (b) (10pts) Write down the log-likelihood and convert it into a minimization problem over the cross-entropy loss E. Derive the gradient of E with respect to each wk, i.e., Vwk E(w)