Artificial Intelligence is the study of computer science that makes a machine which can mimic human without explicitly programmed.
Artificial Intelligence, the term was meant to describe the goal that machines will be able to have humans like intelligence in the future. AI term originated in late 1956s.
Machine Learning
Machine Learning(ML) is a subset of Artificial Intelligence(AI).
Machine Learning has the ability to learn from experience(data) to solve the real-world problem without being explicitly programmed.
It has the set of mathematical algorithms that train on a data set to make predictions or take actions in order to optimize some problem.
It has mainly three types:
- Supervise Learning
- Unsupervised Learning
- Reinforcement Learning
Python Library for Machine Learning
To solve the Machine Learning problem for that data gathering, cleaning and visualization must be done. For that bellow python library, you should learn first.
NumPy
Matplotlib
- Python Matplotlib Tutorial
- Matplotlib Line Plot
- Matplotlib Histogram
- Matplotlib Bar Chart
- Matplotlib Pie Chart
- Matplotlib Scatter Plot
- Matplotlib Subplot
- Matplotlib Save Figure
- Matplotlib Image Show
- ……
- Course in progress …
Feature Engineering
- Best 6 Methods to Handling Missing Values/Data Smartly – Data Cleaning
- One Hot Encoding & Dummy Variables | Categorical Variable Encoding
- Feature Scaling – Standardization vs Normalization
- Label Encoding vs Ordinal Encoding | Categorical Variable Encoding
Machine Learning Project
- Machine Learning Project End to End: Student Mark Prediction
- Directing Customers to Subscription Through Financial App Behavior Analysis
- Breast Cancer Detection Using Machine Learning Classifier
- House Prices Prediction Advanced Regression Techniques | Kaggle Competition
- Bangalore House Price Prediction Machine Learning Project till Deployment
Seaborn
- Python Seaborn Tutorial
- Seaborn Line Plot
- Seaborn Histogram
- Seaborn Barplot
- Seaborn Scatter Plot
- Seaborn Heatmap
- Seaborn Pairplot
- ……
- Course in progress …
Statistics for Machine Learning
Machine Learning Algorithms
- Linear Regression
- Root Mean Square Error
- Ridge and Lasso Regression
- Polynomial Linear Regression
- Support Vector Regression
- Support Vector Machine (SVM) Classification
- Decision Tree Classification
- Decision Tree Regression
- Random Forest Classification
- Random Forest Regression
- K Nearest Neighbor Classification
- K Nearest Neighbor Regression
- Naïve Bayes Classifier
- Save & Load Machine Learning Model