Week1 Study guides, Class notes & Summaries

Write a formal report on your findings from the last several weeks for the regression problem of the Nutrition Case Study. The main objective is to write a fully executed R-Markdown program performing regression prediction using the best models found for and comparing the cost functions and R-square values. Make sure to describe the final hyperparameter settings of all algorithms that were used for comparison purposes. Perform EDA on MNIST and Fashion MNIST data and share your findings in the...

Ensemble predictive models Write a fully executed R-Markdown program and submit a pdf file solving and answering questions listed below under Problems at the end of chapter 13. For clarity, make sure to give an appropriate title to each section. Problem 2: eBay auctions (a, b, c, d) Problem 3: Predicting delayed flights (a, b)

The objective is to write a formal analysis report finishing the objectives set forth in the final case analysis document. A sample template for the final report is provided that contains minimum requirements for the report including the following sections: Introduction, Analysis and Results, Methodology, Limitations and Conclusion. You are required to follow the report template and explain the findings including final models ran for the task.

Create a chart showing the words with the greatest contribution to positive or negative sentiment in the AP articles. Show all the code from the necessary packages untll you can produce the chart. Comment your code line by line. Create charts showing the terms with the highest tf-idf from each of four selected inaugural addresses. Eliminate the ? term. Show all the code from the necessary packages untll you can produce the chart. Comment your code line by line. Create charts showing over time...

1. Show stacked bar charts of the most common terms within each of 2 topics from the Associated Press articles in the topicmodels package. Color the charts by topic. Comment your code line by line. 2. Show a stacked bar chart showing the words that have a Beta greater than 1/1000 in at least one topic with the greatest difference in Beta between topic 1 and topic 2. comment each line of your code.

NRNP 6566 WEEK1-5 Midterm Latest (Answered) 100% Verified 1. Describe cytochrome p450 system {{ANS}}Cytochrome p450 system is a series of enzymes used to metabolize medications 2. Inhibitors {{ANS}}block metabolic activity from one or more CYP450 enzymes 3. Inducers {ANS}}increase CYP450 enzyme activity by increasing enzyme synthesis 4. Describe effect on low and high albumin levels on active drug levels especially for drugs that are highly protein bound {{ANS}}Albumin is the plasm...

1. load the broom library 2. use tidy() on the out dataframe to produce a new dataframe of component level information. Store the result in out_comp. 3. round all the columns to two decimal places using round_df(). 4. Produce a flipped scatter plot of Term v. Estimate 5. Produce a new tidy output of out including confidence intervals. Store it in a variable called out_conf after rounding the dataframe to two decimals. 6. Remove the intercept column and the term continent from the label and ...

1. pipe the election data through the select() function to pick out the following columns - state, total_vote, r_points, pct_trump, party, census. Pipe that through sample() to see the first five rows. 2. Create a state level dotplot of election data except the District of Columbia faceted by region. Colorize the dots by party and insert a vertical line dividing the parties, scale the x axis from -30 to +40, put the states on the y axis and label each facet by region and the entire set by ...

1. load the margins library 2. create a new column called called polviews_m to use Moderate as a reference category using relevel on the polviews column of the gss_sm data. 3. use glm() to create a model called out_bo using logistic regression of polviews_m with sex and race showing an interaction glm(obama~ polviews_m + sex*race, family = "binomial", data = gss_sm). 4. use summary() on out_bo to see what the results look like 5. calculate the marginal effects of each variable and sto...

1. look at the first six rows of the asasec dataset 2. plot members v revenue for 2014 in a scatterplot with a confidence interval 3. switch from loess to ols and add the Journal variable 4. show the first six rows of studebt 5. create a faceted comparison of the two distributions - percent of all borrowers and Percent of all balances to show how student loan debt is distributed. 6. Compare this pair of graphs to the pie charts in figure 8.24 Which visualization do you find it easier to ma...