Write a program that receives two numbers as input from the user. The program should then output the sum of all the numbers including and between the two numbers and the concatenation of all the numbers including and between the two numbers. Ex. input of 1,5   output of 15 and 12345

Danny and Gage trained a Convolutional Neural Network (CNN) to classify 100 different types of industrial components from grayscale images (128×128 pixels). Architecture: Conv1: 64 filters (3×3), ReLU activation Conv2: 128 filters (3×3), ReLU activation Conv3: 256 filters (3×3), ReLU activation Pooling: 2×2 max pooling after every conv layer Fully Connected (FC1): 512 neurons, ReLU Output layer: 100 neurons, softmax Optimizer: Adam (learning rate = 0.001) Batch size: 128 Danny and Gage observed that during training: After initialization, almost all activations in Conv2 and Conv3 are zero. The training loss stops decreasing after just 2 epochs. Changing the learning rate or adjusting Adam’s parameters slightly doesn’t help much. Using standard ReLU only, the training remains stuck. Which of the following statements most accurately explains the behavior observed by Danny and Gage in this CNN training process?

Which of the following statements about the K Nearest Neighbors (KNN) classifier is true?

Amazon wants to automatically analyse customer feedback to improve their products. They provide you with the following raw review data. “The product is amazing! Exceeded my expectations.” “Worst purchase ever. Completely useless.” “It’s okay, nothing special.” “Absolutely fantastic service and fast delivery.” “Not good, but not terrible either.” Answer the following. a) How would sentiment polarity affect this data? b) Propose a method to compute the sentiment polarity of a review. Illustrate your method with review #2. c) Now, consider using a machine learning approach. Outline the steps to train a model for sentiment polarity detection. d) A new review reads: “The product is neither good nor bad.” If your approach returns a polarity score of 0.0, while a trained ML model predicts slightly negative. Explain why this discrepancy might occur.

What is the output? import numpy as np arr = np.array([[10, 20, 30],                [40, 50, 60],                [70, 80, 90]]) print(arr[::2, 1:])

def count_sentences(text):    count = 0    for ch in text:        if ch in “.!?”:            count += 1    return count def avg_word_length(text):    words = text.split()    total_chars = sum(len(word.strip(“,;:”)) for word in words)    return total_chars / len(words) Which of the following statements about the code is true a) count_sentences may overcount sentences if a sentence ends with multiple punctuation marks, e.g., “Nathan!!”b) avg_word_length will raise an error if text is an empty string.c) avg_word_length ignores punctuation like commas, semicolons, and colons, but not periods or exclamation marks inside words.d) Both functions correctly handle all edge cases for English text.

[BUS2] A real estate developer, Ms. Hart, approaches Mr. Lang, an officer of Apex Manufacturing, to ask whether Apex would be interested in purchasing a parcel of land located next to Apex’s main factory. Mr. Lang realizes the land would be highly valuable to Apex for future expansion, but instead personally purchases the property in his own name and later offers to lease it to Apex at a premium rate. Which fiduciary duty has Mr. Lang most clearly violated?

[LIT2] Does the Massachusetts court have personal jurisdiction over W.R. Grace & Co. and Beatrice Foods?

For questions 24 – 25, please refer to the following passage: Michael Jennings is a “reverse engineer” whose business is to buy a product and then reverse-engineer it to find out how it works. Once a job is complete, Michael’s memory is erased by Shorty to prevent him from divulging secrets regarding the reverse engineering process. ARC has recently put on the market a “living monitor” called “A-life” that can display images on a computer display or monitor in three dimensions (3D). Allcom hires Jennings to reverse engineer the A-Life product. Jennings purchases ARC’s A-Life monitor from a store and eventually determines the complicated algorithms and functionality needed to generate A-Life’s 3D images. Jennings passes on the technical details to Allcom, which never had access to the software code, and Jennings is paid a lump sum $526,000.19 paycheck for his work. Allcom eventually begins to sell its holo-monitor, which incorporated similar functions as A-Life’s product performed. Unbeknownst to Allcom, ARC had filed for a U.S. patent prior to Jennings’ reverse-engineering success. The now-issued, valid U.S. patent literally claimed every element of the methods used in Allcom’s product.

[CR1] Who most likely owns the copyright to the software code for the ED209 robot, if there are aspects of the software that are copyrightable?