Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI.
80 Hrs.
Outlines
- Numpy
- PANDAS
- Inferential Statistics
- Data Visualization
- Simple Linear Regression
- Boston house price prediction (PROJECT 1)
- Multiple Linear regressions
- Gradient Descent
- Model Performance Metrics
- Model Selection
- Naive Bayes
- Logistic Regression
- Support Vector Machine (SVM)
- Titanic Survivals prediction (PROJECT 2)
- Ensembles Methods
- Advanced Algorithms
- Finding charity donors (PROJECT 3)
- Final PROJECT EXAM
Prerequisites
Before attending this course, you should have:
- Python skills
- A grounding in enterprise computing
- Be familiar with enterprise IT
- Have a general (high-level) understanding of systems architecture
- Good foundational mathematics in linear algebra and probability
- Any students in college who want to start a career in Data Science.
- Any data analysts who want to level up in Machine Learning