Ans Imran

In 2022 I started the new  Machine Learning Specialization by Andrew NG. I completed it's first two courses in 2022. I'll share the jupyter notebooks from this specialization soon. Now, in 2023 when I am finally free from my M1, I am going to complete the specialization. Here is the fourth Assignment of course 3 (last course) on Recommender Systems.   Procedure : In Content based filtering, for a movie streaming website, we have a set of users and their ratings to the movies they watched. We can also create engineered features e.g, the average rating that a user gave to each genre. We then have another dataset that contains all of the movies and their corresponding average ratings and their corresponding one-hot-encoded genres. The users data is fed into a neural network. The movies data is fed into another neural network. Both neural networks can have different architects, but the final layer of each neural network must be identical to the other one. The final layers give...

  In 2022 I started the new  Machine Learning Specialization by Andrew NG. I completed it's first two courses in 2022. I'll share the jupyter notebooks from this specialization soon. Now, in 2023 when I am finally free from my M1, I am going to complete the specialization. Here is the third Assignment of course 3 (last course) on Recommender Systems.   Problem Statement : 307 measurements of two features throughput (mb/s) latency (ms)  of several servers , were given, to us, we were tasked to find anomalous behavior of a server.   Procedure : Since in addition to unlabelled data, we, also had some labelled data, so, we made a training dataser from unlabelled data and a cross validation set from labelled data. First we used numpy to find the mean and variance of the features. Then we using mean and variance we created probability distribution functions for each feature. Assuming that all features are statistically independent, the total probability for a samp...

  In 2022 I started the new  Machine Learning Specialization by Andrew NG. I completed it's first two courses in 2022. I'll share the jupyter notebooks from this specialization soon. Now, in 2023 when I am finally free from my M1, I am going to complete the specialization. Here is the third Assignment of course 3 (last course) on Recommender Systems.   We were given a dataset which contained 'nu' users and 'nm' movies. The ratings that each user gave to various movies were present in the dataset. The task was: We have a new user who has not yet rated a lot of movies. We have have to recommended him movies based on his previous ratings.   Procedure : The cost function was implemented using For Loop & then without any loop (Vectorized Implementation) A list of movie ratings for a new user was created and was added to the training data The rows(movies) were normalized by taking average of each row for non-zero values and then subtracting each value from the...