Machine Learing with Python

Machine Learing with Python

Introduction

Machine learning and AI, as a unit, are still developing but are rapidly growing in usage due to the need for automation. Artificial Intelligence makes it possible to create innovative solutions to common problems, such as fraud detection, personal assistants, spam filters, search engines, and recommendations systems.

The demand for smart solutions to real-world problems necessitates the need to develop AI further in order to automate tasks that are tedious to program without AI. Python programming language is considered the best algorithm to help automate such tasks, and it offers greater simplicity and consistency than other programming languages. Further, the presence of an engaging python community makes it easy for developers to discuss projects and contribute ideas on how to enhance their code.

Machine learning is a growing technology which enables computers to learn automatically from past data. Machine learning uses various algorithms for building mathematical models and making predictions using historical data or information. Currently, it is being used for various tasks such as image recognition, speech recognition, email filtering, Facebook auto-tagging, recommender system, and many more.

What is Machine Learning with Python?

Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of Computer Programs that can change when exposed to new data. In this article, we’ll see basics of Machine Learning, and implementation of a simple machine learning algorithm using python.

Machine learning is a section of Artificial Intelligence (AI) that aims at making a machine learn from experience and automatically do the work without necessarily being programmed on a task. On the other hand, Artificial Intelligence (AI) is the broader meaning of machine learning, where computers are made to be receptive to the human level by recognizing visually, by speech, language translation, and consequently making critical decisions.

Python is a programming language that distinguishes itself from other programming languages by its flexibility, simplicity, and reliable tools required to create modern software. Python is consistent and is anchored on simplicity, which makes it most appropriate for machine learning. The Python programming language best fits machine learning due to its independent platform and its popularity in the programming community.

Objective of this Training

The objective of this training is to serve as an introduction to machine learning with Python. We will explore several clustering, classification, and regression algorithms and see how they can help us perform a variety of machine learning tasks. We will then apply what we have learned to generate predictions and perform segmentation on real-world data sets. In particular, we will structure our machine learning models as though we were producing a data product, an actionable model that can be used in larger programs.

Learning Objectives

By the ending of this Training, you will be able to:

 The difference between the two main types of machine learning methods: supervised and unsupervised.

 Supervised learning algorithms, including classification and regression.

 Unsupervised learning algorithms, including Clustering and Dimensionality Reduction.

 How statistical modelling relates to machine learning and how to compare them.

 Real-life examples of the different ways machine learning affect society.

Eligibility Required

 BE/BTech. (All Streams)

 BCA, BSc (CS/IT) Degree

 PGDCA, MCA, ME /MTech

On completion of this training, you will be work as -

 Data Analyst - Python

 Machine Learning Engineer

  Data Scientist - Python

  Product Developer

 Technical Data Analyst

 Principal Data Scientist