On behalf of the PATHS-UP Team and R-STEM, welcome to your three week summer internship!!!! We are all thrilled to have such wonderful students working with us this summer. And are even more excited to read about the interesting experiences you will be participating in while you complete your internships. Please use this blog page as a way to share your experience with the world. You may include pictures and videos in each post, and you are encouraged to be as expressive as you wish!
Social Media Tags are encouraged:
@mathematic_AL @RiceU_STEM @PathsUp #PATHSUPYoungScholars
Have fun!!
Allen
Thank you for the instructions. The internship has been going great so far, as I have acquired much knowledge about ML that I never knew about before. Looking forward to working on the project over the next two weeks.
When I applied for the PATHS-UP Youngs Scholars program, I was looking forward to getting the research experience, knowledge in machine learning, a network of like-minded peers, and the chance to work in a program dedicated to improving the accessibility and affordability of health technologies. Now, just after the first few days, I can already say that it is even better than I imagined! Day 1 started off with a warm welcome from our amazing program director Allen and meeting with the other wonderful young scholars. After our orientation, we got to meet with our incredible mentors, Ankit and Bhargav, both graduate students at Rice who were reassuring and patient enough to explain the basics of machine learning and ease us into our research projects. And lastly was our class on Intro to Machine Learning with Dr. Straach, who also patiently explained machine learning and went into even more detail about the subject while also breaking it down for us in an easily comprehensible manner. Throughout the week, we also got to attend insightful presentations and learn more about machine learning. I can’t wait for what the next 2 weeks have in store!
When I first began the internship I was admittedly a bit nervous. However, five minutes into the first day, the nerves were replaced with something much different, excitement. From the enthusiastic words and activities from Mr. Antoine, to the fascinating lecture from Dr. Straach, each moment of the day was filled with knowledge of a field I had previously only dipped my feet into. During our first lecture, the concepts in the reading I had previously reviewed became crystal clear. The distinction of the different types of machine learning to the multitude and diverse ways we use them in our daily lives including Amazon’s top choice for you and Netflix’s recommended shows. So many problems that seemed complex and impossible to understand seemed to unfold before my eyes. I quickly realized that machine learning is not only of great significance, but the future of our world. Moreover, I feel immensely grateful to be able to take part in this internship as it helps give me the skills I will need to one day use machine learning in my own research. While I have previously coded some programs using Java, the coding and knowledge behind a machine learning program require much more creativity and deep thinking. This was easily one of the things that excited me the most. As Dr. Straach explained to us the different types of algorithms that could be used when approaching a supervised learning program and the trial and error required to create an effective machine learning program, I became more and more excited. While, yes the program is a challenging undertaking for me, the ability to challenge myself in such a creative and complex way has been such an amazing experience, and I can’t wait to test the limits on what we can accomplish in these three weeks.
I feel incredibly fortunate to be a part of the 2021 Paths Up Young Scholars program. This week I have met some incredible people and learned more than I could have ever imagined. Namely, I have learned how machine learning can be applied in the real world to support underprivileged communities. For example, machine learning programs can be used to predict whether a breast tissue sample is malignant or benign. Just after one week in this program I see clearly how machine learning can improve lives across the globe by making healthcare more efficient and accesible. I feel empowered and excited to learn more about machine learning so I can support my community. In addition, I have learned more specific details about machine learning this week such as the difference between supervised and unsupervised learning. Supervised learning uses labeled data sets and are best used to classify data or predict outcomes. Unsupervised learning attempts to decipher clusters or associations in data sets that are not labeled. I have also learned about deep learning. Deep learning is a subset of machine learning that attempts to simulate how the brain functions by using artificial neural networks. Deep learning makes use of many layers of information processing in order to train a computer using less human assumptions. This week has been absolutely incredible and I cant wait to see what is to come!
The first introduction to the program was truly like no other. The activities we partook in were unique, from the career guess game where everyone figured me out right away to the Twitter Jamboard. It was a great way to kick off the program. After I realized the exclusivity of PATHS UP, I knew I was surrounded by like-minded and driven individuals who were ready for any task at hand. The Young Scholars program has proven itself to be a very effective program in teaching students how to apply certain aspects of computer science such as AI to problems such as cancer. I can really see myself flourishing in the program over the next few weeks and really see where we can go with our supervised learning team. Our mentor said that anything is really possible as long as we keep that steady pace towards the real complicated topics of the program. I’m very hopeful for the upcoming weeks, as our group is well equipped with the tools and qualities we need to carry out our tasks. (I accidentally commented on the Hello World page instead of this one, so I just copied and pasted it.)