In this article, we will share a guide for beginners to machine learning with python. With this article, you will get to know why do machine learning with python. Also which modules you need to learn for doing machine learning with python.
Machine learning is the use of Artificial Intelligence(AI) that gives systems the capacity to automatically learn and improve from experience without being programmed in a detailed manner. It focuses on the improvement of computer programs that can access data and use it to learn for themselves. Machine learning is the process that powers a considerable lot of services we use today this includes recommendation systems like those on Netflix, YouTube; social media feeds like Facebook and Twitter; voice assistants like Siri, Google Assistant, and Alexa; and many more like these.
So you can assume that what chunk of revenue you can get with machine learning. So let’s start!!
Why Do Machine Learning With Python?
If you have the question why do you learn machine learning with python? Then we have the simple reasons to answer it
- It’s easy to learn. When compared with c, c++ and Java, the language structure of python is less complex. Also, Python likewise comprises a ton of code libraries for ease of use.
- Though it is slower than a portion of other different languages, the data handling limit is extraordinary.
- Open Source! Python alongside R is picking up pace and popularity in the analytics area since both of these languages are open source.
- The great capability of communicating with almost all the third-party languages and platforms.
5 Modules You Need To Learn To Do Machine Learning With Python
After having good knowledge about the following things you will learn to do machine learning with python.
1.Python Libraries Suitable For Machine Learning
As you know, python possesses a vast number of libraries. Libraries are nothing but just a collection of ready-made functions and objects that you can import into your script to invest less time. You need to revise this and mug up the part of Python that is applicable to the machine learning. List of libraries you will need for machine learning with python :
- NumPy
- Pandas
- Matplotlib
- Scikit-Learn
2.Regression
First, get a brief introduction on regression. You need to learn about various methods of regression and their applications. Try to practice these methods on different data sets. Also, learn how to assess your regression model and calculate its precision. Key things need to learn in regression for machine learning with python:
- Simple Linear Regression
- Non-Linear Regression
- Model Evaluation methods or metrics
3.Classification
You need to learn about various classification(grouping) techniques. Practice with various classification algorithms. Also, you can learn about the pros and cons of every technique and different classification accuracy metrics. Key classification techniques you need for machine learning with python:
- K-Nearest Neighbours
- Decision Trees
- Logistic Regression
- Support Vector Machines
- Evaluation Metrics in Classification
4. Clustering / Unsupervised Learning
You need to learn about various clustering approaches. Also learn how to use clustering for customer segmentation, grouping the same vehicles, and also clustering of weather stations. You must have knowledge about 3 main types of clustering for machine learning with python:
- K-Means Clustering
- Hierarchical Clustering
- Density-Based Clustering
5. Recommender Systems
You have to learn about recommender systems(recommendations you get on platforms like youtube, Instagram). At first, you will get presented with the main thought behind recommendations engines, then you understand two main types of recommendation engines. These are:
- Content-based recommender systems
- Collaborative Filtering
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