Lecture 1:
- What is Machine Learning, Supervised Learning, Unsupervised Learning, Deep Learning?
- What is Classification, Regression, Clustering, Anomaly Detection?
Lecture 2:
- Example of Bad data visualization
- Data visualization in Python: Pie Chart, Bar plot
Lecture 3:
- Familiarity with matplotlib and seaborn
- Data Analysis using NumPy and Pandas
- How to find the number of unique values present in the DataFrame?
- How to rename a column name is pandas DataFrame?
- How to round the numeric values in a pandas column?
- How to change the index of a DataFrame?
- How to write functions in Python?
- Data Visualization: Bar plot
- How to change the context of a plot?
- How to create subplots?
- How to set a title, xlabel and ylabel of a plot?
- How to change the range of x and y axis?
- How to rotate the x and y tick labels?
Lecture 4:
- How to create a new DataFrame?
- How to create new column in a DataFrame?
- What is slope?
- What's the equation of a straight line?
- Line plot
- How to draw multiple line charts in the same figure?
- How to change the color, linestyle and marker of a figure?
- How to modify the legend of a figure?
Lecture 5:
- Scatter plot
- Regression line
- Pair plot
Lecture 6:
- Histogram
- Distribution
- ecdf (empirical cumulative distribution function)
Lecture 7:
- Boxplot
- Violinplot
Lecture 8:
- Time-series plot
- Plotly visualization example using AutoVizWidget