Introduce yourself to the deeplearning.ai community - Tell us why you want to break into AI!
My name is Dan, and I'm currently studying for an undergraduate degree in Physics from the University of Cambridge. Put short and sweetly, AI projects excite me as they extend my love for Physics – mathematical description of the world around us. To apply advanced techniques that capture environment evolution, complex patterns in everyday data and much more, shapes innovation.
Currently I have had the time over course breaks to study from the first Andrew Ng ML course, which I found extremely interesting and I cannot wait to get involved with learning and collaborating on these novel ideas more in the future - these courses have acted as part of the reason for me curving my path onto a Masters in Computer Science!
This is Bachu Paul from India. I am newbie in AI/ML/DL. I have been working as a software engineer for past 2 years. I have just finished my first course on machine learning by Andrew Ng at coursera. I am excited to learn this new technology, and I am very much fascinated by the use of AI/ML in many companies from Google to startups.
Looking forward to dive deep into deep learning.
Hi i am Jean-Marc from France.
Back in the 80's i began in automation field as a sort of data science engineer.
Now i am involved in digital tranformation and agile coaching of various teams.
Last year i decided to refresh my knowledge and followed the ML course of Pr Andrew.
When the 5 courses of DL specialization were created i've embarqued in this Journey. It was a very enjoyable and fun Journey.
To refresh and improve my programming skills (preprocessing and vizualisation area) i followed the specialization of amazing Pr. Chuck Severance on Python^^
Since that i am giving Survey on kaggle challenge, a great source of inspiration on architecture NN and using python to manipulate data (Toxic comments challenge and google speech recognition challenge for the moment)
I am not using DL in my day to day work but i began a personal project : estimating user story using ML technics in the agile field.
Having an project is a good way to learn more. For the moment i am working or better to say toying only on 2000 samples which i have collected. But it's a nice way to work on analyzing datas, impacts of outlier, choice of various NN architecture.
Naturally after the end of the specialization, i gave a try to BI LSTM 🙂 but actually i have better result with relative simple CNN architecture!
I also realized the importance of quality of datas (more important than volume in some sense).
Another field of interest is Speech recognition with limited ressources (running in local on raspberry pi for example).
Looking forward to share our passions.
I am IT Architect from India, making a change from developing and designing apps in Java, to AI and Data Science. Have 24 yrs, started off with Mainframe job, in the early 90s, migrated to Bangalore from Kolkata, changed over to java by the turn of the century (01), and now changing over to Data Science. Happy to be able to make this change. Prof Andrew Ng is a inspiration. The way he explains, the challenging assignments to explain the key concepts are just lovely. Did Fortran 77 in late 80s, while doing my B.S in Manufacturing Engg, same matrix operations, numerical methods, remember very much. But two things were missing, computer time, and guidance of someone like Prof Andrew Ng. Well, now happy to have completed his ML and Deep Learning certificates, and what important, didnt stop at that. Keep reading blogs, trying out new things from Medium.com, urls on twitter. Happy to join the Data Science dept of our Company after proving my worth with some Proof of Concepts. Hoping to have a great journey ahead.
my name is Daniel and I am a data scientist at a german social network called Xing. Our team is responsible for several recommender systems including job recommendations and members recommendations. We are currently looking into switching several components to deep learning. The coursera specialisation was a great way of getting more familiar with the material.
Cheers from Hamburg,
My name is Tenzin. I have completed the specialization course in April, 2018. I have learn so much valuable topic and concepts from this course. I got selected in Camber Racing, college team in India as computer vision developer for driverless vehicle to participate in Student Formula Germany Driverless competition. So this course really help me to get started with computer vision and get me through all the project. Now I am the lead of the driverless domian of the team. So I am very thankful the deeplearning.ai courses.
I'm Cátia, I'm from Lisbon, Portugal. I am finishing my master's in Biomedical Engineering, specialized in medical imaging and biosignals. I am currently working as an intern in a research center where I am learning how I can use Deep Learning to predict neuronal activation in zebrafish.
I took the machine learning course from coursera and I am now working my way through the Deep Learning specialization!
Nice to meet you all,
Hi everyone. I'm Soroush from Iran. I'm a Bechelor's student at Razi university right now studying computer engineering. I tried some computer fields like Robotics, Electronics, Networks and Programming, and at last I was enjoying programming(Python language). After 2 years I found machine learning and that was where my life began 🙂 I started with Machine Learning course of Prof. Ng at coursera about a year ago. after that I tried his Deep learning specialization and that was amazing. I felt I can understand everything when watching his videos. there was no special mathematics prior and it helped me to understand concepts as strong as I can. Now I'm passing Hinton's Neural Networks course on coursera and I really suggest it to you if you are interested in learning new things of neural nets.
I'm always interested in make computers conscious and making life easier with AI, so that's why I'm here.
my plan is to finish my bachelor here, and after that apply for master's and PHD in USA or Canada in field AI.
Hello everyone! 🤗
My name is Cesc Canet and I am from Barcelona. I hold a Masters degree in Informatics from Edinburgh University and I did my thesis in Reinforcement Learning methods applied to agent-based computational modelling. I have spent 10 years in industry working in data science, data engineering, machine learning, business intelligence and software engineering.
I completed Prof Ng's Machine Learning Coursera course back in December 2013 (that course was a MOOC baptism for many of us). Five years later, in October 2018 I watched all the courses all over again! The ML course is like a good classical movie that every time you watch it you discover subtle things that make it so exciting to watch it again, and I am sure the same thing will happen with the deeplearning.ai courses.
Many of the techniques I learned in that course helped me a lot at my work. For example, in the a phone number search startup I used the precission/recall/F-score metrics to evaluate several candidate algorithms. We also used some of the spam detection techniques to create a spam call detection service which is now used by milions of users to block robocalls and annoying SMS.
Now I am taking the deeplearning.ai courses and they are opening my mind in so many ways. I enjoy the Python Notebooks and the Quizes a lot because they really help understanding all the concepts very well and they give you a sense of AI empowerment that is so exciting. I feel very excited about CNNs, GANs and Computer Vision now and I would like to explore more these topics and do some research myself. One of the things which I am enjoying the most about it are the "Heroes of Deep Learning" videos as they help you get to know the rockstar researchers and their personal motivations and interests, for example the interviews with Geoffrey Hinton and Yoshua Bengio were so awesome.
I also enjoyed a lot hearing Andrew Ng commentary about the seminal papers on DL (LeNet-5, AlexNet, etc), as it helped me both understanding what was so novel about those concepts when the papers were published and learning how those same problems would be tackled today.
I am interested in learning more about the latest advancements in DL, ML, RL and Comptuter Vision. One of the things I would like to find at the deeplearning community is a commentary of the latest advancements. So for example, if tomorrow there is a groundbreaking result published at a conference or a new kickass technique providing great results in ImageNet , I would like to get to hear more about that paper in a video lecture that is simple to understand, as sometimes reading the papers or arXiv is a bit tedious.
Thanks you to all the people making deeplearning.ai so awesome!
PS: It's just been announced a new course called "AI for Everyone". What a time to be alive!