[P7-DS] My Data Science Path 2019 OCT — 6th week

Subject:Pre Processing data for Machine Learning and depth of ML knowledge .

Photo by Shahadat Shemul on Unsplash

Hello every one welcome back , to the part 6 of my path for data scientist if you haven’t followed my past week blog please read it , so that you can understand how i’m learning and where i’m learning.

1 . About This Past Week

This past week i learned machine learning , boom yeah i said that i won’t move to machine learning until i completely learn the Data Pre processing but trust me there are few things we need to do after EDA , did you got my point yes that’s One Hot Encoder and Label Encoder basically it calls Feature Encoding.And i started learning the

i) machine learning by sentdex - youtube ,

ii) machine learning by Georgia Tech — udacity

iii) Data Lit (theschool.ai) and

iv) many youtube videos

To be frank i already know how most of the algorithms are work , regression , k-means , svm , k-nn , decision tree , Neural Network not the math part , i just know how the things works so i taught i need to learn math so , machine learning by sentdex , is good place to start he teaches math , concept, create from scratch, but he not covering all the algorithms he just covering

linear — regression ,

K-NN ,

SVM ,

K-Means ,

Mean -Shift and

Neural Networks.

2 . How deep a Data Scientist wants to know machine learning:

This is the Question from all learning data scientist right , So when decide to learn ML don’t measure , learn until you get bored .We’re not a ML Engineer right , we just need to know the Model Optimization , Hyper parameter optimization (did i pronounced correct ?) , Yeah because of math , if you’re a math lover (i’m not a math lover) you can learn and create your own from the Scratch with the help of numpy and pandas , but we use SKlearn to create a model and we optimize it , so you need to understand the concept of working principle (with / without [math] try to learn with math) .

3 . Feature Encoding / Selection :

Before moving to Machine Learning make sure that you understand Feature Encoding and Feature Selection , this is very important for the Model Accuracy .

4. About coming week :

I don’t know what i’m going to do , i have two mindset

1 . Learn Machine Learning first ,

2 . Learn Machine Learning first.

5 . Resources of the Week:

Data Lit (theschool.ai) by famous youtuber Siraj Ravel

Past Post:

[P6-DS] My Data Science Path 2019 OCT- 5th weak