https://github.com/edaaydinea/ibmaiengineering
https://github.com/edaaydinea/ibmaiengineering
Last synced: 6 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/edaaydinea/ibmaiengineering
- Owner: edaaydinea
- License: apache-2.0
- Created: 2024-07-19T21:17:40.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-08-22T18:25:55.000Z (about 1 year ago)
- Last Synced: 2024-08-22T20:45:52.217Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 994 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# IBM AI Engineering Professional Certificate
* **Where:** Coursera
* **University/Institute:** IBM
* **Status:** In Progress
## Courses in this Specialization
Course 1: Machine Learning with Python
* **Status:** In Progress
* **Link:** /<>
Course 2: Introduction to Deep Learning & Neural Networks with Keras
* **Status:** Not Started
* **Link:** /<>
Course 3: Introduction to Computer Vision with Watson and OpenCV
* **Status:** Not Started
* **Link:** /<>
Course 4: Deep Neural Networks with PyTorch
* **Status:** Not Started
* **Link:** /<>
Course 5: Building Deep Learning Models with TensorFlow
* **Status:** Not Started
* **Link:** /<>
Course 6: AI Capstone Project with Deep Learning
* **Status:** Not Started
* **Link:** /<>
...
## Courses
### Course 1: Machine Learning with Python
Week 2
* [**Week2 Note**](L1/W2/Week2.md)
* **Assignments**
* [Simple Linear Regression](L1/W2/ML0101EN-Reg-Simple-Linear-Regression-Co2.ipynb)
* [Multiple Linear Regression](L1/W2/ML0101EN-Reg-Mulitple-Linear-Regression-Co2.ipynb)
Week 3
* [**Week3 Note**](L1/W3/Week3.md)
* **Assignments**
* [K-Nearest Neighbors](L1/W3/ML0101EN-Clas-K-Nearest-neighbors-CustCat.ipynb)
* [Decision Trees](L1/W3/ML0101EN-Clas-Decision-Trees-drug.ipynb)
* [Regression Trees](L1/W3/Regression_Trees.ipynb)
* [Credit Card Fraud Detection using Scikit-learn](L1/W3/classification_tree_svm.ipynb)
* [Taxi Tip Prediction using Scikit-learn and Snap ML](L1/W3/Regression_Trees_SnapML.ipynb)
Week 4
* [**Week4 Note**](L1/W4/Week4.md)
* **Assignments**
* [Logistic Regression with Python](L1/W4/ML0101EN-Clas-Logistic-Reg-churn.ipynb)
* [Support Vector Machines with Python](L1/W4/ML0101EN-Clas-SVM-cancer-prediction.ipynb)
* [Softmax Regression, One vs All and One-vs-One for Multi-class Classification](L1/W4/Multi-class_Classification.ipynb)
Week 5
* [**Week5 Note**](L1/W5/Week5.md)
* **Assignments**
Week 6
* [**Week6 Note**](L1/W6/Week6.md)
* **Assignments**
...
## Certificates
* **Course 1: Machine Learning with Python**