AI, ML and DL
Description
Curriculum
Curriculum
- 28 Sections
- 28 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- Artificial Intelligence1
- Introduction of Artificial Intelligence1
- ML with Probability1
- Normal & Property Distributions in ML1
- Normal & Uniform Distributions for Data Science1
- Normal Distribution & Z-Table1
- Hypothesis Testing & Sampling Basics1
- Data Analysis & Statistical Testing1
- Statistical Testing1
- Normal Distribution & Data Sampling1
- Data Analysis & Correlation Explained1
- ML Modeling with Real-World Data1
- Linear Regression & Gradient Descent1
- Visualize Health Data with Plotly in ML1
- Handling Missing Data in Machine Learning1
- Tune ML Models for Accuracy1
- Real Data Cleaning for ML1
- Prepare Data for ML Models1
- ML & Property Investment Basics1
- ML Hinglish Code & Projects Fun1
- ML Preprocessing & Validation Basics1
- ML Basics Clean Data to Predictions1
- ML Workflow in Python Explained1
- ML Fundamentals and Tune Your Models1
- ML Basics to Advanced1
- ata Decisions with ML Tuning1
- Smart Predictions with ML Techniques1
- Efficient ML Classification Models1
Instructor
32 Students12 Courses
Reviews
Price
Free
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