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Leaving the underground
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NIGERIA IS NOT SAFE
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Recent Sessions with some of Africa's brightest minds.
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Doctoral Student @ MIT
HR Manager @ Pernod Ricard Western Africa
Senior Digital Communications Analyst @ Oando Plc
Creative Director @ Thalia Bespoke Nigeria
Senior Writer @ TechCabal
Managing Director & Computer Science PhD Student @ The Diasporic Group & Cornell University
Educator @ Covenant University
International Criminal and Human Rights Lawyer
Senior Lecturer @ The Technical University of Kenya
Personal Brand Therapist | Bus Consultant | Relationship Counsellor | Content Creator @ NEST Consolidated
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Top answers from some of our sessions.
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Hi Isaac, i am glad you find the answers useful. To the first question, finding tailors was a major problem for me mostly because i had no interest in actually sitting on a machine. I personally do not enjoy it. I also started with no direction in mind i just kept saying i wanted to do ready to wear but didn’t think of basic things like the kind of clients i wanted to cater to and how i can get them. The tailors that were very good were expensive, I couldn’t afford them but i went ahead and got one regardless. The business was barely surviving i had to let him go.Knowing your target audience is important so if they aren’t in your immediate circle, you have do something else short term to get noticed by your actual target audience. Getting clients was a problem because my social circle is extremely small and were also in my tax bracket while i was aiming for people outside that bracket.It is also important that whenyou give someone a discount, make sure you tell them it is a discount.Learning and restrategizing is the most important thing. When something isn’t working find a new way. My brand is still evolving and that is fine, till you find what works. For starting up you might not make a lot of profit and that is fine, if you have a long term plan. Might being the keyword, it honestly is not the case for some people. Social capital is a huge determining factor. You want people to notice you and experience your brand once you have that you can start to mark up, those who know your value will stay. Do not take on more than you can handle, it will affect your quality of work and it will mess with you. Activity is not productivity, prioritize things. Learn when to say noAbout staying true to your style I honestly will say you decide that. Nothing wrong in letting other things influence your style. The idea of a business is making money, i also understand that carving a niche is important but if its not working you might need to tweak it till it works.

Yewande Orenuga
Creative Director @ Thalia Bespoke Nigeria
I think this is a bit dangerous. Attempting to ascertain sentimental correlations and apply them to huge financial decisions may work in certain contexts and you could definitely train a model with 99% training accuracy on this task, but future situations that are dependent on complex human action can never be adequately represented by a numerical parameterization and a finite state machine. If the model is not large enough, we will not learn all the possible combinations of interactions. If it is too large, then we only learn the context of our training dataset. That being said, you could do both and get good results during training. Personally, I do not have extensive NLP experience or Bayesian experience in production, but their fundamentals suggest that they would learn this type of model well independently or in conjunction. Naïve Bayes is good for state estimation-based decision making, and NLP can be used to model language and extract sentiment. However, these models depend completely on the input dataset that one utilizes, and the chosen labels (if using a supervised method) that are often subjective. Using data from the internet is also dangerous because it is next to impossible to have humans annotate every piece of training data without spending a large amount of money, and learning from problematic input data can lead to problematic situations.To make this less vague, take the 2016 example where Tay, a chatbot made by Microsoft and trained on Twitter data, became extremely racist in less than a day of online training (https://twitter.com/geraldmellor/status/712880710328139776). Attempting to determine causation in a data driven sense is a slippery slope, and until AI solves the data-driven generalization problem (which I believe may be never) I wouldn't build a system like this in production until I could guarantee significant human supervision and have looked at the ethical implications on those who do not financially benefit from the proposed system.

Ifueko Igbinedion
Doctoral Student @ MIT
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