Mastering Machine Learning with simple baby steps
Our Mission is to make Machine Learning accessible to everyone !
Machine learning is hard. Most content out there is too mathematical or had too much of code that takes the confusion to higher levels. The need is to explain the concepts of Machine Learning and other similar concepts in simple language that anyone can understand
I was overwhelmed with the Tsunami of new mathametical concepts, compounded with having to pick up new programming skills like python / R. So, I tailored this curriculum so that anyone can quickly grasp the concepts and get going
Making use of the Data skills that you already have
We have spent years and years working with data. We will utilize the data skills that we already posses and extend it to train and predict using machine learning. Intended audience: Data Engineers, Analysts and people who are already proficient in SQL. Most of the organizational data resides in relational databases. If you have good experience working with relational databases, you already know how to pull data from disparate sources, cleanse and stitch them together. We will not invent new skills, we will make use of the skills that you already have and see how we can extract value out of it
Why even become a Data Scientist ?
Data Scientist has already been declared as the hottest job, data scientist brings in skill sets and knowledge from various backgrounds such as mathematics, statistics, Analytics, modeling, and business acumen. These skills help them to identify patterns which can help the organization to recognize new market opportunities
- There is huge Demand for Data Scientists and enormous shortage of people
- Attractive Pay (Average salary of 121K$ in the US)
- Companies love when they can make value out of their data
- Its Fun, Exciting and evolving field
- Data Science is flourishing, Its easy to grab a job
Machine learning Myths:
Before we begin our journey, lets bust some myths about machine learning and spread some positive vibes:
- You do not need that Phd degree in statistics to be a machine learning engineer and you do not have to understand all the algorithms. Of course you will need good understanding of numbers and some basic algebra. But take a breath, you can learn all of them eventually
- You do not have to understand everything. Gulping in all the statistics, data prepping, plotting and visualizing, applying algorithms can be overwhelming. So do not try to take them all at once, its okay if you don't get it in the first place, just move on with the tutorial you will learn organically.
- You do not need to be a Python programmer. The syntax of the Python language is intuitive. Try to relate and understand the code, This will get you most of the way. So, Just get started and dive into the details later
- You cannot master everything in Machine learning. Machine learning is a vast subject ranging from computer-vision, natural language processing, advanced-analytics, text-sentiment prediction ... (Don't worry if you cant relate to these terms, you will very soon). Its important that we choose one area and master it.