Today, We are going to going to start our journey in Machine Learning.
Here is the standard definition:
Machine Learning is the field of study that gives computers the capability to learn without being explicitly programmed.
In simple words, It is the process of training the machine or computer on given data and then predicts the result as per our requirements. Because in Machine Learning we are basically building the Machine Learning model on training data and then testing it on test data and then we predict future results. So here we are just teaching the machine, how to learn.
It is used worldwide in different fields of our daily Life, like auto-correct keyboard, product suggestion on online shopping site, Online translators, Augmented Reality (AR), Face Unlock, online chatbots, weather Prediction, data analysis for the stock market, self-driving cars, Robots, etc.
Here is the Machine Learning Models and processes that are quite popular:
- Data Preprocessing
- Logistic Regression
- K-Nearest Neighbors (K-NN)
- Support Vector Machine (SVM)
- Kernel SVM
- Naive Bayes
- Decision Tree Classification
- Random Forest Classification
- Evaluation of Classification Models
- K-Means Clustering
- Hierarchical Clustering
- Association Rule Learning
- Reinforcement Learning
- Upper Confidence Bound (UCB)
- Thompson Sampling
- Natural Language Processing
- Deep Learning
- Artificial Neural Network
- Convolutional Neural Network
- Dimensionality Reduction
- Principal Component Analysis (PCA)
- Linear Discriminant Analysis (LDA)
- Kernel PCA
- Model Selection
But it isn’t limited to this. It has much more things. For more details we recommend to check out the below site:
If you are thinking that what is the relation between, Data Science, Machine Learning, Deep Learning, Artificial Intelligence, etc. Then the following picture will give you a clear idea about it.
We hope this Information will give you the basic Idea about Machine learning.
Please also check out our other blogs: