Difference between revisions of "Watch me Build a Marketing Startup"
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[http://www.google.com/search?q=Bot+Framework+deep+machine+learning+ML ...Google search] | [http://www.google.com/search?q=Bot+Framework+deep+machine+learning+ML ...Google search] | ||
| − | * [[ | + | * [http://nodejs.org/en/ Node.js] - JavaScript runtime built on Chrome's V8 JavaScript engine |
| − | * [[ | + | * [http://reactjs.org/ React] = JavaScript library for building user interfaces |
| + | * [http://www.postgresql.org/ PostgreSQL] Open Source Relational Database | ||
| + | * [http://knexjs.org/ Knex.js] SQL query builder | ||
| + | * [http://graphql.org/ GraphQL] a query language for your API, and a server-side runtime for executing queries | ||
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* [[Natural Language Processing (NLP)]] - [http://primo.ai/index.php?title=Natural_Language_Processing_(NLP)#Sentiment_Analysis Sentiment_Analysis] | * [[Natural Language Processing (NLP)]] - [http://primo.ai/index.php?title=Natural_Language_Processing_(NLP)#Sentiment_Analysis Sentiment_Analysis] | ||
* [[Bidirectional Encoder Representations from Transformers (BERT)]] | * [[Bidirectional Encoder Representations from Transformers (BERT)]] | ||
Revision as of 20:10, 23 April 2019
YouTube search... ...Google search
- Node.js - JavaScript runtime built on Chrome's V8 JavaScript engine
- React = JavaScript library for building user interfaces
- PostgreSQL Open Source Relational Database
- Knex.js SQL query builder
- GraphQL a query language for your API, and a server-side runtime for executing queries
- Natural Language Processing (NLP) - Sentiment_Analysis
- Bidirectional Encoder Representations from Transformers (BERT)
- Firebase | Google's mobile development platform
- AnyChart
- DialogFlow | Google
- TensorFlow
- Alpaca API lets you build and trade with real-time market data for free
- Plaid for users to connect their bank accounts to an app
- Word2Vec
- Siraj Raval's Watch me Build a Finance Startup
I've built an app called VectorFunnel that automatically scores leads for marketing & sales teams! I used React for the frontend, Node.js for the backend, PostgreSQL for the database, and Tensorflow.js for scoring each lead in an excel spreadsheet. There are a host of other tools that I used like ClearBit's data API and various Javascript frameworks. If you have no idea what any of that is, that's ok I'll show you! In this video, I'll explain how I built the app so that you can understand how all these parts fit together. The learning goal here is to give you enough of an idea of how these tools work to be able to formulate a plan for your own marketing startup MVP (minimum viable product). Enjoy! Code for "Watch Me Build a Marketing Startup" | Siraj Raval - GitHub
