The 2019 Year In Review

Source: Deep Learning on Medium

This 2019 year in review is an exercise in looking back and seeing how much has changed in just this one year alone. While I did manage to accomplish a few things, It is the things that I didn’t plan ahead that brought me the greatest sense of fulfillment and the most interesting conversations. I wish this exercise helps me recognize accomplishments as well as setbacks.

Muir woods


I had the privilege of writing 2 technical articles this year. I was not able to write as much as I would have loved to.

  1. Paper summary: Deep residual learning for image recognition
  2. Paper summary: U-net convolutional networks for biomedical image segmentation


  1. I kept working on Nestmetric we raked in revenue. 🚀
  2. Our masterclasses trained more than 20 students. 🚀
  3. I started an investment company with a friend and have a few assets under management. 🚀
  4. Tried building a trading company didn’t take off as expected we will probably pivot and see how that goes.
  5. We started Vumapay, we will be pivoting too.

The last two are experiments and will remain as such until they show significant traction.

Life things and Adventure

I traveled to 2 countries USA and Canada bringing my total country count to 6. What was different about visiting those countries this year is I traveled to different cities, Los Angeles and Vancouver respectively. Having been in San Francisco and Montreal previously.

Family was in good health throughout the year. We thank God!

We also welcomed 2 new members into the family. Growth 🚀

I attended the 420 event at golden gate park, We also hiked the Hollywood hills. The Hollywood walk of fame. Thanks, Andrew for hosting us!

I dropped alcohol — it has been 3 months now!

Mt Hollywood Trail to the Hollywood sign


March — I attended Nvidia GTC GPU Technology conference in San Jose, USA

March — Strata data conference San Francisco, USA

August — Deep learning Indaba 2019 Nairobi, Kenya

August — attended ACCA power of digital roundtable where a friend was a speaker. Nairobi, Kenya

December — Attended Neural Information Processing Systems (Neurips 2019) in Vancouver, Canada. A machine learning and computational neuroscience conference.

Neural Information Processing Systems Neurips Attendance badge


Our poster Deep Learning for game matchmaking optimization was accepted at scipy 2019 Austin, Texas. Unfortunately, I didn’t make it to travel for the presentation.

Learning and School

Attended the University of San Francisco for a certificate in deep learning covering Bottom-up approach: implementation from scratch of pytorch library, Object detection, seq2seq/attention, Transformer/XL, CycleGAN, audio, distributed training, JIT, CUDA, Swift for TensorFlow and conducting research on SoTA algorithms and implementing them.

I dived into Natural Language Processing (NLP) and will see what I can do this coming year with the new skills.

Still haven’t resumed my MSc in econometrics, actually, I will do away with it altogether and pursue other opportunities including but not limited to pursuing a Bachelors’s in Mathematics and Computer Science.


I started the year with the goal of reading 24 books, two books a month. I think I did well, but still fell short. Though it would require a different post to go through the books and the things I learned from each, here is a list:

  1. Think on these things- Krishnamurthi
  2. Radical candor — Kim Scott
  3. Social engineering — Christopher Hadnagy
  4. Never split the difference — Tahl Raz
  5. The daily stoic — Hanselman, Stephen
  6. Chaos monkey — Antonio Garsia
  7. The secret of Sandhill Road — Scott Kupor
  8. The Rational male — Tomassi Rollo
  9. Thinking in Bets -Annie Duke
  10. Bayes theorem (A visual introduction to beginners ) — Dan Morris
  11. The Three-Body Problem — Cixin Liu
  12. Becoming — Michelle Obama
  13. Moonwalking with Einstein — Joshua Foer
  14. Machine Learning with python Cookbook Albon (Technical)

People who had an impact on my life

I’m a private person and this is the hardest part of this post.

My co-founders Duncan and John — We have been through a lot this year together. The lows have been really low and the highs have been really high. You have been real comrades!

“Startup experience does have a certain comrade-in-arms, foxhole quality to it. Nobody believes in what you are doing except this other poor fool sitting next to you, who’s just fucked as you are if you don’t succeed. Nothing is keeping the entity going except your shared delusion”

People I have had interesting conversations and pulled me out of my comfort zone. I called you guys when things were falling apart, you called just to check-in. long walks, morning runs, hikes, cycling, and parties we had, debates that shaped my worldview. You even dared to engage me in topics I know nothing about and in the process, I learned a lot from you guys.

Kena Amoah, Marisa Lin, Andrew Berkowitz, Ben Nyabuti, Cate Gitau, Julius Mwaniki, Aaron Fu, Satya Das, Ashley Karani, Angie Akinde, Shanaya Stephenson, Oliver Yeung, Majorie Ndirangu, Onyinloye Ayodeji, Oluwole Oyekanmi , Kevin, Brian and a lot more people

Things I invested in this year and Why

Safaricom shares — my overall thesis is that this company will continue to grow as it faces almost no significant competition. The data offering will grow significantly as an increase in smartphones and computers grows. On the flip side the data offering could be something they could lose a grip on if facebook, google entered this market as an ISP. (facebook tried but left nothing stops them from coming back again). Small companies competing with Safaricom might continue to exist in the short term but will likely close shop due to sustainability issues given infrastructure cost. Mobile Money transfer will for sure change as crypto goes mainstream and I don’t see mobile money as a competitive advantage in the long run.

Blockchain education — to better understand coins and identify companies building critical infrastructure to solve problems in the space as well as identify new opportunities that will be enabled.

Favors and things I need

  1. I’m looking to meet somebody who embodies wellness, physical fitness, and a healthy lifestyle. I will be hitting the gym daily and doing morning runs once in a while. — most likely this will be my trainer at the gym.
  2. Looking for a mentor someone who knows or has published machine learning papers in major conferences. Their feedback on my research would be greatly appreciated
  3. Looking to meet someone who knows about investing in foreign stocks e.g GOOGL, SNAP, TSLA, etc. and can help with the regulations that come with it.

What I fell short

Lifting – I tried to take up working out and lifting but that never happened in 2019. Will see whether this happens in 2020

1 paper got rejected in conferences

I didn’t read as much as I could have wished too

Planned to hike mt. Kenya. Never happened

Vipassana — was to do a 10-day silent retreat. Unfortunately, I had to travel.


I read a bunch of Machine Learning white papers, this is something I struggled with for a while.

Deep Learning for game matchmaking optimization was accepted at a conference for a poster presentation.

The Future

Looking forward to learning more about building autonomous intelligent machines and systems that will involve acquiring skills in these interconnected areas: Robotics, Vision & Perception; Machine Intelligence & Multi-Agent Systems; Control & Verification; and M2M, Secure Sensing & Actuation.

Build more robust portfolio financial assets and property at personal and investment company level.

Will invest more in cryptocurrencies would rather go long on car manufacturing companies and short on horses.


Writing ✍🏾— I’d like to do more technical writing and teach what I will be learning.

Speaking 🗣— I’d want to give an oral presentation at a conference/ workshop on machine learning

Life 🌏✈️⛰— Travel more, more adventure, more hikes, more beaches

Research 🤖 — I want to write a paper and get it accepted to a top machine learning conference

Learning and Work🎓 — looking forward to studying more reinforcement learning

Reading 📚 — 24 books? This still remains a goal

Wellness🏋🏿 — vipassana, lifting and running planning to get this done this year.

Thanks, everyone who tagged along this journey. 2019 we planted, more planting in 2020!

Happy new year!