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- # Create Custom Transformer Create a custom transformer, just as we did in the lecture video entitled "Custom Transformers", that performs two computations: 1. Adds an attribute to the end of the numerical data (i.e. new last column) that is equal to $\frac{x_1^3}{x_5}$ for each observation. In other words, for each instance, you will cube the $x_1$ column and then divide by the $x_5$ column. 2. Drops the entire $x_4$ feature column if the passed function argument `drop_x4` is `True` and doesn't drop the column if `drop_x4` is `False`. (See further instructions below.) You must name your custom transformer class `Assignment4Transformer`. Your class should include an input parameter called `drop_x4` with a default value of `True` that deletes the $x_4$ feature column when its value is `True`, but preserves the $x_4$ feature column when you pass a value of `False`. This transformer will be used in a pipeline. In that pipeline, an imputer will be run *before* this transformer. Keep…l JO 100 4G 2:02 AM @ 52% assignment_3 v2 AI and ML Assignment 3 Write a python program to cluster candidates into 2/3 groups. The program performs dimensionality reduction, then clustering of candidates based on top 2 PCs. The results are plotted to visually show the performance of candidates. The program performs the following tasks: Read input "pca cluster.csv" file. Use Panda library. Example of the file: candi cand2 cand3 cand4 cand5 cad6 experience 10 9 7 3 education 10 10 8 10 health 4 6 8 9 9. interview 9 6 6 8 7 test 4 9. 10 communication skills 7. 6 9 10 10 writing skills team player leadership 10 9 6 6. 8 7 4 10 9 4 10 4 9 6 8 5 9 7 enthusiasm 7. 7 7 9 ready to start 5 6 6. 9 1 flexible in hours 10 1 9. 5 6. able to relocate 6 6 6. 10 4 references 9 9 7 9 4 10 • Apply PCA analysis to identify top 2 PCs. Eigen No. 0 Eigen value (33.50+0j) Contribution % (40.87+0j) Points on new scale [5 5-8 3 0-5] Eigen No. I Eigen value- (22.65+Oj) Contribution % (27.63+0j) Points on new…please code in python A mining company conducts a survey of an n-by-n square grid of land. Each row of land is numbered from 0 to n-1 where 0 is the top and n-1 is the bottom, and each column is also numbered from 0 to n-1 where 0 is the left and n-1 is the right. The company wishes to record which squares of this grid contain mineral deposits. The company decides to use a list of tuples to store the location of each deposit. The first item in each tuple is the row of the deposit. The second item is the column. The third item is a non-negative number representing the size of the deposit, in tons. For example, the following code defines a sample representation of a set of deposits in an 8-by-8 grid.deposits = [(0, 4, .3), (6, 2, 3), (3, 7, 2.2), (5, 5, .5), (3, 5, .8), (7, 7, .3)]Given a list of deposits like the one above, write a function to create a string representation for a rectangular sub-region of the land. Your function should take a list of deposits, then a set of parameters…
- PLEASE ONLY DO THIS TYPEWRITTEN. THANK YOU. SKIP IF YOU ALREADY DID THIS.Take a array of 10 size and fill it with multiplication table of 10 and then print the whole array.. You must use loop. In NIM PROGRAMMING LANGUAGEdef apply_gaussian_noise(X, sigma=0.1): """ adds noise from standard normal distribution with standard deviation sigma :param X: image tensor of shape [batch, 3, height, width] Returns X + noise. """ ### YOUR CODE HERE ### # noise tests theoretical_std = (X_train[:100].std() ** 2 + 0.5 ** 2) ** .5 our_std = apply_gaussian_noise(X_train[:100], sigma=0.5).std() assert abs(theoretical_std - our_std) < 0.01, \ "Standard deviation does not match it's required value. Make sure you use sigma as std." assert abs(apply_gaussian_noise(X_train[:100], sigma=0.5).mean() - X_train[:100].mean()) < 0.01, \ "Mean has changed. Please add zero-mean noise"
- Q.Create an interesting educational information chat box that asks the user to give an input question and then answers the question given by user with a suitable answer. It should match the question of user with a suitable answer avaliable . You can make use of list for different questions and answers. (if possible) Save two to three answers for a single question and then for random selection of elements from those answers use random choice(list) method from random module that returns a random element. Also for a user question that doesn't matches with the questions present in the chat box it should display statement like "oops i can't answer that" "sorry i am not intelligent enough" "could u please ask something else" using random method so that every time one of these statements appear **coding language python ***try using basic programming techniques in python without using arrays and pointers * * * copy paste the program itself and also the screenshot of program and output…Q.Create an interesting educational information chat box that asks the user to give an input question and then answers the question given by user with a suitable answer. It should match the question of user with the answer avaliable. Make use of list for different questions and answers. (if possible) Save two to three answers for a single question and then for random selection of elements from those answers use random choice(list) method from random module that returns a random element. Also for a user question that doesn't matches with the questions present in the chat box it should display statement like "oops i can't answer that" "sorry i am not intelligent enough" "could u please ask something else" using random method so that every time one of these statements appear **coding language python ***try using basic programming techniques in python without using arrays and pointers * * * copy paste the program itself and also the screenshot of program and output * * * use any…Iterating over a dictionary example: Gradebook statistics. Write a program that uses the keys(), values(), and/or items() dict methods to find statistics about the student_grades dictionary. Find the following: Print the name and grade percentage of the student with the highest total of points. Find the average score of each assignment. Find and apply a curve to each student's total score, such that the best student has 100% of the total points. The language is in Python. # student_grades contains scores (out of 100) for 5 assignmentsstudent_grades = {'Andrew': [56, 79, 90, 22, 50],'Nisreen': [88, 62, 68, 75, 78],'Alan': [95, 88, 92, 85, 85],'Chang': [76, 88, 85, 82, 90],'Tricia': [99, 92, 95, 89, 99]} So far I have the first part of the question: for student, scores in student_grades.items(): print(student, sum(scores)/len(scores))