ravikanthstats

oday, we engaged in a discussion centered around the dataset, with a focus on two key machine learning algorithms: K-Means clustering and K-Nearest Neighbors (KNN). The professor explained the underlying concepts, applications, and differences between the two methods. Additionally, we were introduced to Ravi Pakalpati’s thesis, which was discussed in the context of its relevance to our ongoing work and the methodologies it employe

On 29th March, we received feedback on our Project 1 submission. The feedback highlighted certain areas that required improvement. Following this, our group had a constructive discussion with the professor to gain clarity on the suggested changes and understand how we could enhance the quality of our report. This conversation provided valuable insights that will help us make the necessary revisions effectively.

Today, we had a discussion focused on the dataset for Project 2, which closely mirrored the conversation we had last week. During the session, we were given the opportunity to share our individual ideas, interpretations, and initial thoughts regarding the dataset. This collaborative exchange helped us deepen our understanding of the data and explore potential directions for our analysis moving forward.

Today, we held a detailed discussion regarding the newly introduced ACLED-India dataset. The conversation focused primarily on understanding the structure and characteristics of the dataset, particularly the various attributes it contains. We explored the meaning and relevance of each attribute, how they are defined, and how they can be utilized for analysis. This initial review was aimed at building a foundational understanding of the dataset to guide future analytical work and research.

Today we had an interactive secession where professor G Davis is asking every group about the project status and prof asked about our project and and we briefly described him about our project .

Today our classmate Mahnoor presented her ideas where she was talking about the percent of people shot at a county and how are they shot continuously over the period of time.

Today we discussed various topics related to statistics, like standard deviation, standard normal distribution and the had a discussion about inference based questions (comapring to fields like age , race etc )

In our third lecture we had a discussion about the washington shooting data set. I had few questions regarding the

How many of the individuals shot had prior criminal records? Does past criminal history correlate with the likelihood of being involved in a police shooting?
What was the outcome of police shootings in terms of legal actions taken against officers involved? Were they prosecuted or disciplined?
Policy Recommendations & Impact
How does Washington compare to other states in terms of police shooting rates? What policies do lower-shooting states have in place that Washington can adopt?
Have there been any significant changes in police shooting trends before and after policy reforms (such as body camera mandates, use-of-force training, or mental health crisis intervention)?

Today we were discussing about the Washington shooting dataset, various questions from students are taken ,the questions and concepts are discussed in a brief manner by professor G Davis.

On the first day, we did an introduction to the course: course texts, instructional videos, and assessment criteria. We were also guided on how to create a WordPress account using our college credentials, which we would use to do our journaling throughout the course.