C coding project that needs a rework. Works up to part 3 but i included parts 1,2,3 for context. There are bugs that need to be fixed for part 3 and comments on how the code works need to be added. PLEASE ONLY QUOTE FOR coding part 4! Communicate further if you want to do it.
To compile in terminal, go into directory and hit ‘make’/make clean to run/clean makefile.
Research Report Outline The report outline should be one page long. Use font Times New Roman, size 12, approximately 250 words. No full sentences should be used Use bullet points Include all APA in-text citations (quotes and paraphrases) in the outline
You must select and use AT LEAST 2 sources from the list given for your chosen topic. Wikipedia will not be accepted.
– write Background and discussion.
– Please write the idea on your own words
Please get information from these two links:
https://hbr.org/2018/08/to-make-self-driving-cars-safe-we-also-need-better-roads-and-infrastructure https://www.thenational.ae/uae/transport/first-driverless-car-hits-the-streets-of-dubai-1.924115
https://www.theguardian.com/commentisfree/2019/feb/13/the-self-driving-car-is-a-marvel-doomed-by-unpredictable-humans
https://www.ft.com/content/0ec3079c-0b9d-11ea-8fb7-8fcec0c3b0f9
For this assignment you will design and create a year-long weight loss program. You will provide a snap shot of each month along with commentary.
Guidelines:
Client background age, weight loss goals, any health issues
Program
12 snapshots
Discussion of activities for the month
Strength training summary
Conditioning summary
Auxiliary training summary
Specifics should be mentioned, but you do not need to present an entire program for each month. For example, core lifts have progressed from 70% and 3×10 10,8,6 at 75, 80, 85%.
Progressive overload should be present
Strategies to maintain exercise adherence
Write a Python 3 program called pa1.py that implements a three-class linear classifier using the following method:
Training (using the training data set):
1. Compute the centroid of each class (e.g. A, B, and C).
2. Construct a discriminant function between each pair of classes (e.g. A/B, B/C, and A/C), halfway between the two centroids and orthogonal to the line connecting the two centroids. This is the basic linear classifier that we have discussed.
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