Day by day make incremental progress on iterations, working collaboratively whether that be solo or together.
Team-Goals: Be respectful of each other's time
I have been contemplating switching careers for some time, and finally committed to Turing after deciding that now was indeed the right time. Previously, I had been working sales roles in a variety of industries: logistics, financial services, electronics. Part of the reason I stayed in sales roles was because of my strengths in communicating and connecting with people, but ultimately, I did not flourish in those roles because they did not appeal to my creativity and problem-solving abilities.
My life has had bumps along the way, and I think in some ways the hesitation to go back to school stemmed from the fact that I do not have a safety net. I was extremely fortunate to come out of college with a moderate sum of debt but had been anxious in adding on to the sum by taking out a loan to go back to school. After some consideration however, it felt like a greater risk to continue down the path I was headed ending in an unfulfilling career, and potentially an unfulfilling life. I figured that if given 7
SwapiTrivia Group Member Names: Cameron MacRae and James Miller
Goals and Expectations for the Project (What does each group member hope to get out of this project? What do we want to achieve as a team? How will we know that we're successful?): Day by day make incremental progress on iterations, working collaboratively whether that be solo or together.
Team-Goals: Learn some shit.... have good grasp of the learning objectives and try to have proficient on as many of the grading rubrics as possible. GET THAT SCROLLING TEXT FUNCTIONALITY!!
Team strengths & collaboration styles (consider discussing your Pairin qualities here):
RancidTomatillos Group Member Names: Colin Koga, John Adams, James Miller
Iteration 5 would be a good goal to shoot for. We learned all the objectives Before we move on to the next iteration make sure to have the testing, and refactoring in place.
This gist is a resource for anyone who may be learning about Redux for the first time, or would like to learn more in depth about Redux and the Redux cycle. It will begin with a brief observation and explanation of the core tenets of the Flux application architecture. Next, it will dive into how Redux is a Flux implementation, examining its core defining features, and explaining why and when you may want to consider having it be a part of your client-side applications. Finally, it will conclude with a step-by-step explanation of the Redux cycle and how all the individual parts interact.
I think for right now the git squash and rebase sounds like something that could be beneficial in keeping the commits from bloating out of control. When working on a larger codebase, with a lot of developer working in tandem, I think git log will be helpful in allowing me to understand the changes that have occurred while working on a branch.
From my understanding merging would be like shuffling a deck of cards by combining them in order chronologically, where as rebase would be taking a slice of cards(commits) and putting them atop the rest of the deck(master).
The topic I have selected for my differentiation assignment is Artifical Intelligence. While I have had some prior experience in the subject (started Andrew Ng's Machine Learning course available on Coursera many moons ago), in my recent research I have found that there are many terms in the field that get thrown around but the differences may not be explicitly understood. At least, that was the case for me. Thus, the objective of this gist will be to briefly explore and define the following terms and how they are alike and different: Artificial Intelligence, Machine Learning, Neural Networks and Deep Learning.
