Machine Learning Course
Deepen ML knowledge: algorithms, pipelines, evaluation metrics and practical projects.
Duration:
3 Months
· Level: Beginner
Seats Available
24
Supervised Learning
Unsupervised Learning
Feature Engineering
scikit-learn
XGBoost
TensorFlow (intro)
Jupyter
What you'll learn
Deepen ML knowledge: algorithms, pipelines, evaluation metrics and practical projects.
Course Curriculum
- Linear regression, logistic regression
- Bias-variance tradeoff
- Evaluation metrics
- Decision trees
- Random Forests & Boosting
- Hyperparameter tuning
- Pipelines & feature engineering
- Model interpretability
- Intro to deep learning concepts
Modules
- Foundations of ML
- Tree models & ensembles
- Pipelines & evaluation
Career Opportunities
- Machine Learning Engineer
- Data Scientist
- Research Associate
Machine Learning Course
Focused machine learning course covering algorithms, feature engineering, model evaluation and pro...
Rating
(3)
Duration
3 Months
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