https://github.com/edaaydinea/mathematicsformlanddatascience
https://github.com/edaaydinea/mathematicsformlanddatascience
Last synced: 7 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/edaaydinea/mathematicsformlanddatascience
- Owner: edaaydinea
- License: apache-2.0
- Created: 2024-07-12T17:13:40.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-08-26T19:13:22.000Z (about 1 year ago)
- Last Synced: 2024-08-26T22:28:04.699Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 10.4 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Mathematics for Machine Learning and Data Science Specialization
- **Where:** Coursera
- **University\Institute:** DeepLearning.AI
- **Status:** In Progress
## Courses in this Specialization
1. Linear Algebra for Machine Learning and Data Science
- **Status:** Completed
- **Link:**
2. Calculus for Machine Learning and Data Science
- **Status:**Not Started
- **Link:**
3. Probability & Statistics for Machine Learning & Data Science
- **Status:** In Progress
- **Link:**
...
## Course Notes & Programming Activities
### Course 1: Linear Algebra for Machine Learning and Data Science
- **Week 1: Systems of linear equations**
- [Introduction to Python Matrices and NumPy](L1/W1/C1_W1_Lab_1_introduction_to_numpy_arrays.ipynb)
- [Representing Systems of Equations as Matrices](L1/W1/C1_W1_Lab_2_linear_systems_as_matrices.ipynb)
- **Week 2: Solving systems of linear equations**
- [Introduction to the Numpy.linalg sub-library](L1/W2/C1W2_UGL_solving_linear_systems_3_variables.ipynb)
- [Gaussian Elimination](L1/W2/C1W2_Assignment.ipynb)
- **Week 3: Vectors and Linear Transformations**
- [Vector Operations: Scalar Multiplication, Sum and Dot Product of Vectors](L1/W3/C1W3_UGL_1_vector_operations.ipynb)
- [Matrix Multiplication](L1/W3//C1W3_UGL_2_matrix_multiplication.ipynb)
- [Linear Transformations](L1/W3/C1W3_UGL_3_linear_transformations.ipynb)
- [Linear Transformations and Neural Networks](L1/W3/C1W3_Assignment.ipynb)
- **Week 4: Determinants and Eigenvalues**
- [Interpreting Eigenvalues and Eigenvectors](L1/W4/C1_W4_Lab_1_Interpreting_eigenvalues_and_eigenvectors.ipynb)
- [Eigenvalues and Eigenvectors in Python](L1/W4/C1W4_Assignment.ipynb)
### Course 3: Probability & Statistics for Machine Learning & Data Science
- **Week 1: Introduction to Probability and Probability Distributions**
- [Lecture Note 1](L3/W1/lecture_note1.md)
- [Monty Hall Problem](L3/W1/C3_W1_Lab_1_Monty_Hall.ipynb)
- [Birthday Problem](L3/W1/C3_W1_Lab_2_Birthday_Problems.ipynb)
- [Lecture Note 2](L3/W1/lecture_note2.md)
- [Intro to Pandas World Happiness](L3/W1/intro-to-pandas-world-happiness.ipynb)
- [Rideshare Project](L3/W1/Rideshare_Project_Week1.ipynb)
- [Naive Bayes](L3/W1/C3W1_Assignment.ipynb)
- **Week 2: Describing probability distributions and probability distributions with multiple variables**
- **Week 3: Sampling and Point estimation**
- **Week 4: Confidence intervals and Hypothesis Testing**
- **Week 2: Describing probability distributions and probability distributions with multiple variables**
- [Lecture Note](L3/W2/lecture_note.ipynb)
- [Summary statistics and visualization of data sets](L3/W2/C2W2_UGL_datasets.ipynb)
- [Exploratory Data Analysis - Data Visualization and Summary Statistics](L3/W2/Rideshare_Project_Week2.ipynb)
- [Lab: Simulate Dice Throws with NumPy](L3/W2/C3W2_UGL_Dice_Simulations.ipynb)
- **Week 3: Sampling and Point Estimation**
- [Lecture Note](L3/W3/lecture_note.ipynb)
- [Lab: Central Limit Theorem](L3/W3/C3W3_UGL_Central_Limit_Theorem.ipynb)
- [Lab: Exploratory Data Analysis - Linear Regression](L3/W3/linear-regression-world-happiness.ipynb)
...
## Certificates
- [**Course 1: Linear Algebra for Machine Learning and Data Science**](https://coursera.org/share/1b394cac27a8c72f89cf972124ed381e)