Aggregate Intellect

Build Deep Learning Products, Attract More Opportunities

THEME: Ml IN CLIMATE AND SUSTAINABILITY

In 4 weeks you will:

Step 1: Extend your “ML Product Dev” knowledge

Step 2: Build one for a real-world problem

Step 3: Win Cash Prizes

Techniques: AI Product Development, MLOps and Engineering,

Computer Vision, Natural Language Processing, Graph Neural Networks, Search

COHORT #9 BEGINS MAY 17TH

Free Baseline Participation

STAY COMPETITIVE

Attract opportunities by strengthening and diversifying your portfolio by showing your experience in building ML products for real life problems

BUILD ML PRODUCTS

Solve interesting business problems (your own or a sponsored project idea) in a structured and guided experience

WIN CASH PRIZE

Work with a team of 2-3 peers to solve a business challenge using AI and win prize money when your MVP is selected as the best solution!

ACCESS EXPERTS

Get guidance from a technical lead (senior industry practitioner or academic researcher) as you go through the build process

ACCESS CURATED CONTENT

Access our entire library of expert curated content to find short videos explaining technical concepts and sample code (**paid monthly subscription; cancel any time)

BUILD COLLABORATIVELY

Meet and team up with peers on our platform to solve the problems together. Interact weekly with the sponsoring company (startup founders, usually) to get feedback.

Use Cases & Cash Prizes

$5,000 Prize

How might we achieve super-resolution in satellite imagery for agricultural purposes? tap to see more ...
The goal is to build a module that can ingest low-resolution satellite imagery, ideally from the Sentinel-2 satellites, and generate realistic-looking images that are free of clouds, largely free of artifacts or errors and have an apparent resolution on the meter-scale.
Apply to Join

$1,000 Prize

How might we recommend the most relevant GitHub repos based on a few papers selected by the user? tap to see more ...
Build a recomender system that considers 3+ scientific papers selected by the user about similar concepts, identifies what those concepts are, and uses that information to suggest the most relevant GitHub repos related to those
Apply to Join

How does it work?

1. Select your Project

  • See the details of each sponsored project, or sign up to build your own end to end ML application
  • Sign up to unlock the next steps including team formation preferences, proposal submission 
  • Get access to the “pre-cohort” slack channel for questions

2. Submit a Proposal

  • Use the template provided to put together a proposal for what project you want to work on 
  • Watch AI Product Development video series  to get a better idea about what to put in the proposal
  • Submit! If your proposal is accepted, you will be invited to participate in the cohort.

3. Go through the Product Journey

  • Access the product journey dashboard to make weekly progress report submissions and get feedback
  • Completing the project on your own is free, but as you go you could also purchase various types of support (content, expert access, …) if needed
  • Make a final submission for a chance to win the challenge cash prize

More Info

Familiarity with the following is expected:
  • Python: pandas, scikit-learn
  • (Optional) PyTorch
  • Jupyter Notebook
  • Stats, ML & Neural Nets
“Do I need a good laptop for this challenge?”
  • While that’s nice to have, you could use  Google Colab for the majority of the tasks
  • Google Colab is a zero-configuration environment with free access to cloud GPU’s. Just make sure you have the latest chrome or firefox browser installed.
  • Recommendations for extra resources are available through the product journey dashboard

Need clarification about the prerequisites? 
Join our Slack Community!

You can then either post your questions in #website-support or DM Amir Feizpour 

  • Data Scientists
  • Machine Learning Engineers
  • Product Managers
  • Software Engineers

Questions / not sure if you make the cut? 
Join our Slack Community!

You can then either post your questions in #community-questions or DM Amir Feizpour 

  • Cohort Begins: Mon, May 17th
  • Last Chance to Submit Proposal: Friday, May 14th
  • Final Submission Deadline: Sunday, June 13th

Product Journey

Week 1

>> Finalize your dataset

>> Validate your assumptions through exploratory data analysis

>> Build a base model

Week 2

>> Do an alpha release based on your base model

>> Collect user feedback and improve your base pipeline

>> Hand-on MLOps video series and expert access available to monthly subscribers

Week 3

>> Get more feedback, improve your pipeline

>> Start incorporating advanced ML components 

>> Hands-on advanced ML packages available to monthly subscribers

Week 4

>> Get more feedback and Improve your pipeline

>> Get ready for your final demo

>> Clean up / finalize your code and demo video

>> Submit your entry for the competition!

FAQ'S

At the moment our sponsored competitions are only open to the residents of Canada, United States, and Europe. We are working with our lawyers to expand this. 

If you are from other areas, you could still participate in independent capstone build or other paid or free activities.

Not particularly! Obviously, the more you know the better. But, part of our philosophy is "learning by doing" (ehm, I mean "experiential learning" - to be fancier than necessary). So, you will be learning a #$#$h load from your peers as you try to build things together. All we need you to bring is your ambition, curiosity, and well, enough coding skills. You will also have the option to purchase our expert curated video and code packages, as well as access to private office hours with experts when you sign up for monthly subscription (CAD$19.99 per month)

There is no catch. We believe that building impactful products in emerging tech is something that most people should get exposed to sooner or later. Besides we charge companies who post problem statements a premium fee that enables us to keep it free for developers. 

I mean, we can't really stop you if that's what you want! BUT do we encourage it? Not really!!! There is *SO* much learning in doing things together with peers. However, we understand that some folks prefer that. You can select your preference during the sign up

Since this is a service that is provided for free, in order to ensure high quality of the participants, we expect the "project proposal" as proof of work. Therefore our primary metric for accepting proposals is thoroughness. In other words, your submission doesn't need to be advanced as much as it needs to demonstrate your effort in understanding the problem statement well with information available to you and your effort to plan the project as much as possible. 

The Prizes will be awarded by a panel of judges consisting of representatives of the Sponsor (50%) and our community experts (50%) based on the following:

  1. Effort put in (problem discovery, data collection, training, etc)
  2. Readiness of the solution (can it be used locally or non-locally by many people? how much work is needed for the solution to become minimally viable?)
  3. Optimization (how quickly can your solution perform inference? Points may also be awarded for training optimizations, such as transfer learning.)
  4. Interpretability (how easy is it to explain why your solution works?)
  5. Performance (how well does your solution perform in terms of accuracy - may be a combination of objective and subjective metrics, or other unsupervised performance metrics).
  6. Practicality of the application (is what you built solving an interesting practical problem in a way that can be used by intended users?)
  7. Technical soundness (are you using the right evaluation metrics? Are you using the right algos? Are you interpreting your results correctly?)
  8. Originality & Creativity (were you able to reframe the problem, or perhaps collect / synthesize data, in a creative manner which sidesteps some of the more challenging obstacles? Did you have an original approach to solving the problem or sufficed to overly done approaches?)
  9. Clarity of communication (is it easy to follow your story, and technical detail in your deck and video?)
  10. Quality of production (is the audio/video quality of your final deliverable acceptable) 
  11. Commercial Use (does your solution use copyright or proprietary material, or is it available with an unrestricted license?)
  12. Code Quality (is your code easy for other engineers to understand and modify?)

We estimate around 10 hours a week, but it really depends on your base level, and how much effort you want to put in. It also depends on how effectively you "divide and conquer" with your team members.

Join our community slack workspace, just hang out there and use all our free content until you're ready. Post any questions you have in #cohort8-support (or DM Amir Feizpour). Alternatively, check out our Discussion Groups

If you are working on a company sponsored project, you would be pre-assigning all intellectual property to them. If your solution is not chosen as a winner, you can still publish your work publicly for your portfolio as long as you respect all confidentiality and data privacy terms you agree to as part of the competition. This concretely means that if you don't win, you can remove all references to the sponsor company (their name & brand, any results obtained from their confidential data, all original data they provided and data you derived from their data, any specific details about their use case, etc) and then publish your work publicly.

A lot of our users join our cohorts to add something to their personal / professional portfolio, or refine their ideas for that awesome venture they've been dreaming about. Since we really like ambitious people like you, aggregate intellect doesn't have any claims over the IP you generate as part of our cohorts. It is all yours! all of it!!! 

Past Projects

Aggregate Intellect Stories

You're in Good Company

Our community and partners attract an incredible range of AI & ML practitioners looking to stay ahead of the curve. Below are a few selected companies / universities our users represent.