AI for Technical Founders: Day 0
Why, How, and What?
There is an industrial revolution taking place
Lately AI based startups and products have been dominating our social feeds, Product Hunt, news, and Ted Talks, occupying our own apartments with conversational assistants like Alexa and soon will be taking over a ton of jobs…
History of the word “Sabotage” There is a theory related to the origin of this word. French Luddites used to throw their wooden clogs into powered looms to clog the machinery at the time of the Industrial Revolution.
We are on the verge of an industrial revolution. We, as founders, should take on the responsibility to act on what the future holds to inspire the world around us. More realistically, for the love of god, can we please put all that high-school/college math to use?
The right amount of passion & material
Just like any other subject you want to pursue properly, you need the right amount of passion and the material to begin your journey. Here are few things which got me inspired:
A must watch TED Talk:
AI Experiments by Google: https://aiexperiments.withgoogle.com/
Books (credit goes to Anthony @ GIPHY)
- (Hands-on / Python / $$) https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X/ref=sr_1_8?ie=UTF8&qid=1475703584&sr=8-8&keywords=machine+learning
- (DL / free & online) http://neuralnetworksanddeeplearning.com/
- (DL / free & online) https://github.com/HFTrader/DeepLearningBook
- (Neural Networks / AMAZING! / $$)
- (Stats $$) https://www.amazon.com/Think-Stats-Exploratory-Data-Analysis/dp/1491907339/ref=sr_1_3?s=books&ie=UTF8&qid=1479691133&sr=1-3
- (Stats $$) https://www.amazon.com/Think-Bayes-Bayesian-Statistics-Python/dp/1449370780/ref=sr_1_4?s=books&ie=UTF8&qid=1479691133&sr=1-4
- (Hands-on / Python / Stats / $$) https://www.amazon.com/Elements-Statistical-Learning-Prediction-Statistics/dp/0387848576/ref=sr_1_16?ie=UTF8&qid=1475703584&sr=8-16&keywords=machine+learning
- (Hands-on / R / Stats / $$) https://www.amazon.com/Introduction-Statistical-Learning-Applications-Statistics/dp/1461471370/ref=sr_1_13?ie=UTF8&qid=1475703584&sr=8-13&keywords=machine+learning
- (free & highly recommended / ML) https://www.udacity.com/course/intro-to-machine-learning--ud120
- (free & pretty intense / DL) https://www.udacity.com/course/deep-learning--ud730
- (free / ML) https://www.coursera.org/learn/machine-learning
- (free / heavy on Math / covers almost every subject / MIT)
- (Hands-on / Python / $$) https://www.udemy.com/data-science-and-machine-learning-with-python-hands-on
- (Stats / ML / $$) https://www.udemy.com/data-science-logistic-regression-in-python/learn/v4/
- (Stats / ML / $$) https://www.udemy.com/data-science-linear-regression-in-python/learn/v4/
- (DL / $$) https://www.udemy.com/data-science-deep-learning-in-python/learn/v4/
- (DL / $$) https://www.udemy.com/data-science-deep-learning-in-theano-tensorflow/learn/v4/
- (DL / $$) https://www.udemy.com/deep-learning-convolutional-neural-networks-theano-tensorflow/learn/v4/
An open source project, which will help Fundraising, PR and BD using AI
My goal is to create a tool for founders to help them with Fundraising, while learning/polishing my skills. Often times the most challenging part of fundraising is identifying the right investors. AngelList, Crunchbase, Linkedin and your network is great, but I want to be able to answer these questions:
- Step 1: Supervised & Unsupervised Clustering “Which investors are connected and closely interacting with each other?”
- Step 2: Some NLP & Sentiment Analysis “What investors/VC firms are excited about, what is hot?”
- Step 3: Relevancy & Search “Which investors are more likely to invest in a particular industry?”
- Step 4: Network Analysis “How am I connected to this investor, and who can potentially send a warm intro for me?” — Having a shared LinkedIn connection is often insufficient.
I am sure the roadmap will change as we go along, but for now at least I have a goal and a set mission to go after.
Lets build something cool together!