What are the steps involved in Machine Learning ?

Easy ways to start and to know about Machine Learning ,

Let see example below to visualize how above steps in action ,
Suppose we want to determine difference between Wine and Beer. How do we differensiate in terms of Color or Alcohol percentage ? . We need to have a data from different glassess of Beer and Wine .

Prepare a data in table format or graph in terms of color , % of Alcohol and Beer or Wine. Need to a choose a model as there different models created by Data scientists for Text, Speech , Images , colors and sequences. Then it comes a Traning which is most important part of ML. By Choosing a model we are able to differensiate between Beer and wine rather than depends of human judgement.

For training we have equation
y (output) = m (slope) * x (input) + b (Y-intercept)
weights = [m1,1 m1,2]
biases = [b1,1 b1,2]
Model is nothing but random values of matrix [W,b]
Training data -> Model [W,b] -> Prediction -> Test &Update W,b = Repetitive process

Actual steps of ML
1. Gathering Data
2. Preparing that Data
3. Choosing a Model
4. Training
5. Evolution
6. Hyperparameter Tuning
7. Prediction

Appplications of Machine learning 

1.Detecting cancer,
2. Self driving cards
3. Detecting escalators in need of repair
4. Diabetic Retinopathy

Market size
It will rech $8.81 Billion by 2022 as per reports published by MarketsandMarkets

Want to get your hands dirty in ML use this API ,
TesorFlow is an open source software library for Machine Intelligence. Here is to play around API.


Image source: webtrends