Notes and Projects of the "Data Science and Machine Learning" Course from Udemy
- Analyzing the relationship between LSD consumption and performance on Math Tests
- reference: https://ascpt.onlinelibrary.wiley.com/doi/abs/10.1002/cpt196895635
Gradient Descent I
- Simple Cost function
- Slope and Derivates
- Gradient Descent function
Gradient Descent II
- Multiple Minima vs Initial Guess & Advanced Functions
Gradient Descent III
- Divergence and Overflow
Gradient Descent IV
- Learning Rate
Gradient Descent V
- Data visualization and 3D Charts
Gradient Descent VI
- Partial Derivatives & Symbolic Computation
- Batch Gradient Descent with SymPy
- Graphing 3D Gradient Descent & Adv Numpy Arrays
Gradient Descent VII
- MSE
Gradient Descent VIII
- 3D MSE
Multivariable Regression I
- Gather Data points and features
- Data exploration with Pandas DataFrame
Multivariable Regression II
- Visualizating data
- Histograms, Distributions and Bar Charts
Multivariable Regression III
- Histograms
Multivariable Regression IV
- Descriptive Statistics
Multivariable Regression V
- Correlation
Multivariable Regression VI
- Split training and test dataset
- Multivariable Regression
- Data Transformations
- Regression using log prices
Multivariable Regression VII
- Testing for Multicollinearity
- Model Simplification and BIC
- Residuals and Residual Plots
Bayes Classifier I
- Reading files
- Email body extraction
- Data Cleaning
- Locate empty mails
- Add document IDs
- Remove System file entries from DataFrame
Bayes Classifier II
- Spam Massages visualized
Bayes Classifier III
- Natural Language Processing
- Wordclouds
Bayes Classifier IV
- Generator function
- Missing Data
- Tokenisation
- Generate features and sparse Matrix