Participate in Demo Day.

Getting something:

• Opportunity to get partnering
• Networking opportunities, having access to contract manufacturing

=> Conrad Challenge, $600 each, $1200

User conversation

• Spoke again with CompassionKind: wanting to get 20 units shipped out
• Spoke with SustainableEnergy for All: started by one of the UN reps. of an African country; wanted to have us featured on Social Media
• Wanted to connect
• Start diving into user connections

Hiring requests

In this experiment, an efficient and accurate network of detecting automatically disseminated (bot) content on social platforms is devised. Through the utilisation of parallel convolutional neural network (CNN) which processes variable n-grams of text 15, 20, and 25 tokens in length encoded by Byte Pair Encoding (BPE), the complexities of linguistic content on social platforms are effectively captured and analysed. With validation on two sets of previously unexposed data, the model was able to achieve an accuracy of around 96.6% and 97.4% respectively — meeting or exceeding the performance of other comparable supervised ML solutions to this problem. Through testing, it is concluded that this method of text processing and analysis proves to be an effective way of classifying potentially artificially synthesized user data — aiding the security and integrity of social platforms.

grid search is a hyperparameter tuning technique by trying pairs of all hyperparemeters sequentially

components

• a set of constituent objects
• an operation

requirements for group

• closed: if \(a,b \in G\), then \(a \cdot b \in G\)
• existence of identity: there is \(e \in G\) such that \(e\cdot a= a\cdot e = a\), for all \(a \in G\)
• existence of inverses: there is \(b \in G\) for all \(a \in G\) such that \(a\cdot b = b\cdot a = e\)
• associative: \((a\cdot b)\cdot c = a\cdot (b\cdot c)\) for all \(a,b,c \in G\)

additional information

identity in group commutates with everything (which is the only commutattion in groups