Forecast Future Demand of Phone Using Predictive Analytics

Python Machine Learning

What you’ll learn:
40 videos to take you from beginner to machine learning engineer
Learn meaning of variable and data types in Python
Learn to declare and initialize variable in Python
Converting string to integer and integer to string in Python
Create list in Python and appending to a list
Create Numpy array, one dimensional Array and to convert one dimensional Array to two dimensional Array
Write condition statement in Python
Learn to use loop for performing iterating activity
Perform simple operations on dataset using Python
Understand meaning of Scikit learn, Pandas, Numpy and Matplotlib
Use Pandas to load dataset on Jupyter notebook
Visualizing data using Matplotlib
Analyze data using Pandas and Matplolib
Handling missing values using Pandas
Preprocessing of data using Pandas and scikit learn
Handling Duplicates using Pandas
Data conversion using Pandas
Converting dataframe to datetime
How to create a project and an application in Django
Important configuration for Django project
Learn the relationship between Views, URL and templates in Django
Understand meaning of machine learning and Predictive analytics
Feature selection in machine learning
Use train test split function to divide dataset into training and testing set
Train machine learning algorithm using training set
Use predictive analytics to discover the pattern and forecast the future
Measure accuracy of machine learning algorithm using cross validation
Make prediction using created model in machine learning
Create Django web application for deploying machine learning model
Learn to deploy machine learning model on Django web framework

Requirements
Python Basics
Machine Learning Basics
Visual Studio code, Sublime Text Editor And Pycharm
Computer with minimum of 4 RAM and 250 HDD.
Anaconda Navigator

Description
Become Artificial Intelligence Engineer.

This is step by step course on how to create predictive model using machine learning. It covers Numpy, Pandas, Matplotlib, Scikit learn and Django and at the end predictive model is deployed on Django. Most of things machine learning beginner do not know is how they can deploy a created model. How to put created model into application? Training model and getting 80%, 85% or 90% accuracy does not matter. As Artificial Intelligence Engineer you should be able to put created model into application.

Actually, learning how to deploy predictive model created by machine learning is big win for you and is motivating effect towards improving, embracing and learning machine learning. They piece me off when I hear people saying Artificial Intelligence is not really. It is just theoretical study. Let’s learn together how to deploy model, solve people’s problems and change people’s mind about Artificial Intelligence.

At the end of this course, you will become Artificial Intelligence by your ability to put created model into application and solve people’s problems. Not only that you will be exposed to some few concepts of Django which is Python web framework and current trending web framework. By understanding Django, you will be able to deploy your previous created model you you could not in the previous time.

Who this course is for
Beginner to Python
Beginner to machine learning
Beginner to Predictive Analytics
Beginner to Data science
Beginner to Artificial intelligence