Introduce yourself to the deeplearning.ai community - Tell us why you want to break into AI!
Hi All. I am a reserve military officer and full time employee of a large bank where I manage the global etrading platforms (ecosystem). I live in New York, which I love, with my wife and 3 kids. I have experience in Machine Learning and Python, and just finished a Masters program in Quantitative Finance. I have focused my time now to AI and everything AI, learning and exposing myself to what ever I can. I am also engaged in several AI consortiums as well; trying to find a fit for AI within banking. Good luck to all!
I am Kelvin Chan. I completed the Deep Learning Specialization earlier this year and currently a course mentor for the 2nd course. I am interested in applying deep learning to a current application I am working on, and these courses have helped me tremendously to get started. I am happy to get to know more people in the field.
hi, nice to meet everyone! My name is LiangYou. I have recently relocated back to China after 10+ years of studying and working in United States. I used to work as a financial data analyst at Bloomberg and now I'm working on a project that aims to promote health by motivating folks to do more workout (primarily take more steps). I have always been interested in AI since I joined Bloomberg where there's quiet some efforts on that front. I truly believe AI is the future - it's gonna be the next drastic force that would change every aspect of human's life and make the world a better place. Want to learn more about it.
My name in Vincent from France. I have a software engineering background and more recently I was a pre-sales leader in the data storage and data management arena. I am currently learning new technologies like ML and DL. I really enjoyed Dr Ng's Machine Learning course which I took in July this year. Then I took the Deep Learning Specialization in August. I have some free time at the moment so I was able to complete both in 2 months. I am currently learning more things about Apache Spark. I am really interested by the link between big data analytics and machine/deep learning technologies. They are both coming together as algorithms do need data and data do need algorithms to generate valuable insight.
All the best,
My name is Peter from Nigeria currently starting my Phd in Philosophy in Spain - I intend to work on vagueness in the area of logic and language.
Before philosophy my experience has been programming in python for data mining - cleaning, transforming, text mining, went into natural language processing using libraries but no machine learning and deep learning. I took some online courses and read some articles on ML and DL but haven't applied it in real life.
Instead, I got fascinated with what is language and that was what took me into philosophy. I wanted to look at the whole panorama (NLP, ML, DL) from a philosophical perspective but still link it back to the technical angle. Let's say I wanted to understand the person in order to make the machine better. Of course with the aim of making the machine better in order to make the person's life better.
Okay, enough rambling, my hope here is to see how with your help I can link this panorama (NLP, ML, DL) with vagueness for my Phd thesis 🙂
I am a new data science guy in New Jersey USA with a math undergrad degree with operations research / management science concentration. Originally a general software engineer, using lots of prog languages, for a long time for commercial and military, I am now focusing my work on machine learning. Figuring out new tech, and just doing it, is a common hacker ethos and I am not that different.
Since 2014 I completed around 25+ MOOCs and specialization certs in data sci, machine learning, deep learning, produced by Microsoft, University of Washington, Johns Hopkins University, Harvard U, Stanford U, Univ of Illinois, and most notably our favorite specialization of all, Andrew Ng's Deep Learning Specialization!
The Johns Hopkins Data Science Specialization also was a good one for material coverage, if not quite quality of presentation at times, very complementary to Deep Learning Specialization, because JH Data Science Spec. has broader coverage and more topics beyond just machine learning, like reproducible research. Recommended.
TensorFlow, both graph mode and eager mode, is sometimes good and fast, but too often very annoying and just WAY too long to develop with to get particular challenging features operating correctly. I already wrote lots of original, working TF code, but I am still evaluating whether to discard it and move my work to Micrsoft CNTK or PyTorch or Julia at this time.
I like to develop papers and studies, as well as machine learning software, which are 2 pretty different uses of machine learning.
I will enjoy taking questions from the forum about all the above as well as parallel software, ie, high performance, which I have background in. Operations Research esp Linear Programming, for solving combinatorial problems with linear constraints and objectives, is another area I will enjoy discussions.
I hope to talk with anyone to explore exciting applications of deep learning.
Hello, I’m AnnMargaret. A mobile and web software engineer, I took the Deep Learning Specialization to employ DL in my projects and research.
I look forward to presenting my Grow With Google Android Capstone Project (“DeepBlock” - a Blockchain app that employs Stochastic Weight Averaging and Blockchain miners to decentralize network training in a more energy efficient way) at upcoming NIPS 2018 conference workshops in Montreal.
I look forward to getting to know fellow ML/DL enthusiasts coming aboard this platform.
My name is Eric Quist. I have a PhD in Electrical Engineering, with an emphasis on Detection and Estimation Theory and Controls. Over the last year, I've discovered the Machine Learning work and have been taking the deeplearning.ai courses in order to get into the field. While my academic research and professional work hasn't involved deep learning directly, many of the signal processing techniques and real-time algorithms I've implemented (on FPGAs and GPUs) have a large amount of similarities to the AI community. I look forward to exploring Neural Networks.
I am Jayanthi and am an Architect from Minneapolis, MN, in healthcare industry. I started my machine learning journey a year back with some internal courses at the company and Machine Learning course by Andrew Ng. I have done calculus in my school/college and was able to understand and connect lot of concepts. I am enjoying this stretch effort for me. I am on the 4th course in the specialization. I am working more on tutorials and yet to get to a real project.
I usually do this course on weekends and one afternoon my high school daughter who is doing calculus was watching me do this course. I was doing activation function section and she got curious on what I am doing with derivatives etc. She was very excited to hear about "tanh" function being used actually. She is currently figuring out her college direction and I think this is going to have a significant influence.
My name is Josef, I live in Frankfurt/ Germany and work for a local asset manager. I had my first experience in machine learning with Prof. Ng´s Stanford Machine Learning course on Coursera and Prof. Hastie/ Tibshirani´s Statistical Learning course on Stanford Lagunita in 2014. Since then I practically learned to develop, test and implement models for different purposes like supporting evidence-based decision making to build reliable and cost efficient workflows or most exciting, to predict financial returns in various asset classes. I have subscribed to Prof. Ng´s Deep Learning Specialization to find out how to unlock more accurate inference for complex relationships from big data while getting over the problem with asymptotics. Besides I´d like to get more insights on the possibilities that may arise in my profession with different architecture types of Deep Learning.
My name is Nuriel and I'm from Israel. I was exposed to machine learning in 2014 because of Andrew Ng's MOOC. Completed his machine learning course and the current deep learning specialization.
lately, I implemented an artificial neural network to identify people at risk for PTSD.
I am Michael Johansen and I am a freelance software developer based near Copenhagen, Denmark.
After doing some initial research and testing using neural networks in computer security I did the 5 course specialization at Coursera. I am now also doing the Machine Learning course to learn more about unsupervised learning etc.
My name is Jousef and I am a mechanical engineer from Germany in my Masters where I mainly focus on turbulence modeling for fluid mechanics. I hope that my Machine Learning journey that I recently started on Coursera as well as my deeplearning.ai courses that will follow help me to apply AI to fluid flow behavior and do some small side projects besides that also to improve my Python skills where I consider myself a noob in it so far 🙂
Wish you guys a pleasant AI voyage!
My name is Huy. I'm from Vietnam, an absolutely undeveloped country. I'm 19 years old and currently a computer science student.
Almost the Vietnamese people are farmers, my family too. My parents are quite used to physical labors. They work all day and all night, about 14 hours in low condition. I want to study hard, to be successful to help not also my parents but all the Vietnamese people work with higher productivity. No longer will everybody work with exhaustion and boredom. Besides, the time can be shortened.
So i knew Artificial Intelligence is a field interesting and hepful. I studied very hard to have a good mark, to study at a technical university. So i chose Computer Science. I've asked many people like older students who were researching on AI/ML/DL or professors. I started out in Machine Learning course by Professor Andrew Ng. He teaches in a very easy way. Besides, recently i've been learning Deep Learning on deeplearning.ai. I'm so happy because the course instructor is still professor Andrew Ng. He's absolutely the best.
I belive in a bright future for AI/ML/DL. Also, the Deep Learning course is really great. I learn everyday.
Hi all, my name is Ish.
I am in the final week of the specialization. It was an amazing experience and I have gained significant understanding of several topics of Deep Learning.
I have an MBA degree in Finance but I have always felt that I am unable to use my skill set to contribute towards the development of our society. I left my job to pursue some personal projects but I didn't had much success. While studying about new technologies, I found out about Deep Learning. The more I read about it, the more I was certain that this field has the potential to transform our society. I am trying to gain a deeper understanding of this field by devoting my full time towards it. I hope that I would be able to apply what I have learnt, in creating innovative applications which can alleviate some of the problems of our society. I would thank the complete team of deeplearning.ai for creating this specialization which has helped beginners like me to learn about such a complex topic. Thank you.