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Machine Learning Full Course For Beginners | Machine Learning Tutorial | Machine Learning Course

Great Learning via YouTube


– What Is Machine learning? Introduction to Machine Learning
– Why Machine Learning?
– Road Map to Machine Learning
– How to Use Kaggle
- NumPy Python Tutorial How to Create NumPy Array
- How to Initialize NumPy Array
- How to check the shape of NumPy arrays
- How to Join NumPy Arrays
- NumPy Intersection & Difference
- NumPy Array Mathematics
- NumPy Matrix
- How to Transpose NumPy Matrix
- NumPy Matrix Multiplication
- NumPy Save & Load
- Python Pandas Tutorial
- Pandas Series Object
- Pandas Dataframe
- Matplotlib Python Tutorial
- Line plot
- Bar plot
- Scatter Plot
- Histogram
- Box Plot
- Violin Plot
- Pie Chart
- DoughNut Chart
- SeaBorn Line Plot
- SeaBorn Bar Plot
- SeaBorn ScatterPlot
- SeaBorn Histogram/Distplot
- SeaBorn JointPlot
- SeaBorn BoxPlot
– Role of Mathematics in Data Science
– What is data?
– What is Information?
– What is Statistics?
– What is Population?
– What is Sample?
– What are Parameters?
– Measures of Central Tendency
– Understanding Empirical Rule
– What is Mean, median, and mode?
– Measures of Spread Understanding Range, Inter Quartile Range & Box-plot
– Types of Machine Learning Supervised, Unsupervised & Reinforcement Learning
– How does a Machine Learning Model Learn?
– Supervised Machine Learning Mukesh Rao
– Python for Machine Learning
– Linear Regression Algorithm Hands-on
– What is Logistic Regression
– Linear Regression vs Logistic Regression
– Naïve Bayes Algorithm
– Diabetes Prediction using Naïve Bayes
– Decision Tree and Random Forest Algorithm
– Introduction to Support Vector Machines SVMs
– Kernel Functions
– Advantages & Disadvantages of SVMs
– K-NN Algorithm K-Nearest Neighbour Algorithm
– Introduction to Unsupervised Learning - Clustering
– Introduction to Principal Component Analysis
– PCA for Dimensionality Reduction
– Introduction to Hierarchical Clustering
– Types of Hierarchical Clustering
– How does Agglomerative hierarchical clustering work
– Euclidean Distance
– Manhattan Distance
– Minkowski Distance
– Jaccard Similarity Coefficient/Jaccard Index
– Cosine Similarity
– How to find an optimal number for clustering
– Applications Machine Learning

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Great Learning


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