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This Republic day I tried to do something creative and made an Indian Flag with Turtle using Python. Turtle is a pre-installed Python library. It enables users to create pictures and shapes by providing them with a virtual canvas.
TOP 10 SQL Concepts for Job Interview
Aggregate Functions (SUM/AVG)
Group By and Order By
JOINs (Inner/Left/Right)
Union and Union All
Date and Time processing
String processing
Window Functions (Partition by)
Subquery
View and Index
Common Table Expression (CTE)
TOP 10 Statistics Concepts for Job Interview
Sampling
Experiments (A/B tests)
Descriptive Statistics
p-value
Probability Distributions
t-test
ANOVA
Correlation
Linear Regression
Logistics Regression
TOP 10 Python Concepts for Job Interview
Reading data from file/table
Writing data to file/table
Data Types
Function
Data Preprocessing (numpy/pandas)
Data Visualisation (Matplotlib/seaborn/bokeh)
Machine Learning (sklearn)
Deep Learning (Tensorflow/Keras/PyTorch)
Distributed Processing (PySpark)
Functional and Object Oriented Programming
Data Science Topics: CRISP – DM - Project Management Methodology Exploratory Data Analytics (EDA) / Descriptive Analytics Statistical Data Business Intelligence and Data Visualization Plots & Inferential Statistics Probability Distributions (Continuous & Discrete) Hypothesis Testing - The ‘4’ Must Know Hypothesis Tests Data Mining Supervised Learning – Linear Regression, OLS Predictive Modelling – Multiple Linear Regression Lasso and Ridge Regressions Logistic Regression – Binary Value Prediction, MLE Multinomial Regression Advanced Regression for Count Data Data Mining Unsupervised Learning - Clustering Data Mining Unsupervised Learning - Dimension Reduction (PCA) Data Mining Unsupervised Learning - Association Rules Recommendation Engine Network Analytics Machine Learning - k - NN Classifier Decision Tree & Random Forest Ensemble Techniques - Bagging and Boosting AdaBoost & Extreme Gradient Boosting Text Mining & Natural Language Processing (NLP) Machine Learning Classifier Technique - Naive Bayes Introduction to Perceptron, Multilayer Perceptron Building Blocks of Neural Network Deep Learning Black Box Technique - Neural Network Deep Learning Black Box Technique - SVM Survival Analytics Forecasting/Time Series – Model Driven Algorithms Forecasting/Time Series – Data Driven Algorithms
Machine Learning with Graphs, Leskovec
The Laplace Transform: A Generalized Fourier Transform
’Introduction to Statistics for Data Science, Exploratory Data Analysis in Python‘
Distributions
Probability Mass Functions
Cumulative distribution functions
Modeling distributions
Probability density functions
Relationships between variables
Estimation
Hypothesis testing
Linear least squares
Regression
Time series analysis
Survival analysis
Analytic methods
Credit: Allen B. Downey
XGBoost Tutorials:
You can also refer to the YouTube video tutorial for better understanding:
GitHub Repo:
Blog link:
1-Introduction to Time Series and Forecasting
2-Statistics and Analysis of Scientific Data
3-Linear Algebra Done Right
4-Linear Algebra
5-Algebra
6-Understanding Analysis
7-Understanding Statistics Using R
8-An Introduction to Statistical Learning
9-Statistical Learning from a Regression Perspective
10-Robotics
11-Regression Modeling Strategies
12-A Modern Introduction to Probability and Statistics
13-The Python Workbook
14-Machine Learning in Medicine — a Complete Overview
15-Introduction to Data Science
16-Applied Predictive Modeling
Data Science Process
Data Visualization in Business
Know Machine Learning Key Terminology
Understand Machine Learning Implementation
Machine Learning Applications on Marketing and Retail
1-The Elements of Statistical Learning
2-Introductory Time Series with R
3-A Beginner’s Guide to R
4-Data Structures and Algorithms with Python
5-Introduction to Statistics and Data Analysis
6-Principles of Data Mining
7-Computer Vision
8-Data Mining
9-Robotics, Vision and Control
10-Statistical Analysis and Data Display
11-Statistics and Data Analysis for Financial Engineering
12-Stochastic Processes and Calculus
13Statistical Analysis of Clinical Data on a Pocket Calculator
14-Clinical Data Analysis on a Pocket Calculator
15-The Data Science Design Manual
16-An Introduction to Machine Learning
1-Introduction to Boosted Trees 2-Distributed XGBoost with AWS YARN 3-Distributed XGBoost with XGBoost4J-Spark 4-DART booster 5-Monotonic Constraints 6-Random Forests in XGBoost 7-Feature Interaction Constraints 8-Text Input Format of DMatrix 9-Notes on Parameter Tuning 10-Using XGBoost External Memory Version (beta)
