Crack Data Science (Must know concepts)

Languages : Python or R
R vs Python

Get good grip in python language. It eases and help in many ways

I prefer Python because

• Speed
• Syntax
• ease in production systems

Data Structures in python

• Arrays
• List
• DataFrame
• Dictionary
• Tuples
• Sets

Key packages in python

• Numpy
• Pandas
• Matplotlib
• Scipy
• Scikit-learn
• others also there........
• Pytorch (Neural Networks)

Some of must know concepts

BrodCasting
Distributions - Normal, T-distribution, Bernoulli
Hypothesis testing
Central limit theorem
Supervised vs Un-Supervised
Loss functions
Bias / Variance tradeoff
Missing data analysis - Imputation methods
Linear Algebra
what is reshape(-1,1)

Dot product
Validation techniques
k-fold validation
Stratified k fold
Stacking

Linear Regression
Logistic Regression
Tree based models

Adjusted R-squared
P-value explanation
Storing model in pickle file


Hyper parameters
Model parameters

GridSearchCV
RandomizedSearchCV

Regularization
ROC/AUC
Lasso - L1
Ridge - L2
Elastic Net


Decision Trees
Entropy
Information gain
CART

ensemble models

Bagging - Random Forest
Boosting - XGBoost, Lightgbm
Stacking

PCA
Factor analysis