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__Machine Learning:__

__Machine Learning:__

Welcome to python

**, This is second part of my blog post. In this crash course we will cover the following point:***Machine Learning section*### Syllabus for the Machine Learning:

**1] Linear Regression with python**

**2] Logistic Regression in python**

**3] K- Nearest Neighbors with python**

**4] Decision Trees and Random Forest with python**

**5] Support Vector Machine**

**6] K- Mean Clustering**

**7] Principle Component Analysis**

**8] Recommend System**

### Some Introduction of Syllabus Topic:

1.

**Linear Regression with python:****Linear Regression**is

**machine learning**algorithm based on supervised

**learning**. It performs a different

**regression**task.

2.

**Logistic Regression in python:****Logistic regression**is also supervised

**learning**classification algorithm used to predict the probability of a target variable.

3.

**K- Nearest Neighbors with python:**
The

**K**-**nearest neighbors**is a type of supervised machine learning algorithms. KNN is algorithm used for complex classification.
4.

**Support Vector Machine:**
In machine learning, support-vector machine are supervised models with associated learning algorithm that analyze data used for classification

5. **K- Mean Clustering:**

**K**-

**means clustering is**simplest and popular unsupervised machine learning algorithms. it's also used for clustering classification.

6.

**Principle Component Analysis:****Principal components analysis**is a technique used to emphasize variation and bring out strong pattern in a dataset. It's often used to make data easy to explore and visualized.

**(PCA)**

7.

**Recommend System:**
Recommend Systems is a subclass of information filtering system that seeks to predict the "rating" or preference a user would give to an item. They are primarily used in commercial applications.

8.

**Natural Language Processing:****Natural language processing**involves the reading and

**understanding**of spoken and written

**language**through the medium of a computers.

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