Python Machine Learning Tutorial (Data Science)
Programming with TANSH_CODES
Machine learning is a subset of artificial intelligence or artificial intelligence.
This tutorial will teach you how to build a model that can learn and predict the
kind of music people like. By the end of this one hour tutorial you will have a
good understanding of machine learning basics. You do n't need any prior knowledge
in machine learning but you need to know python fairly well. Machine learning has
other applications in self-driving cars and robotics language processing vision
processing forecasting things like stock market trends and the weather games and so
on so that 's the basic idea about machine learning next we 'll look at machine
learning in action a machine learning project involves a number of steps the first
step is to import our data which often comes in the form of a csv file. We 're
going to look at the popular python libraries that we use in machine learning
projects the first one is numpy which provides a multi-dimensional array. pandas is
a data analysis library that provides a concept called data frame. matplotlib is a
two-dimensional plotting library for creating graphs and plots. scikit-learn is one
of the most popular machine learning libraries that provides all these common
algorithms like neural networks and neural networks.
Anaconda is that it will install jupyter as well as all those popular data science
libraries like numpy pandas and so on so we do n't have to manually install this
using pip all right now as part of the next step anaconda suggests to install
microsoft vs code we already have this on our machine so we can go with continue
and close the installation. in this notebook we can write python code and execute
it line by line. Kaggle. com is a popular data set that we 're going to use in this
lecture. Create an account you can sign up with facebook google or using a custom
email and password once you sign up then come back here in the search bar search
for video game sales this is the name of a data set called vgsales. csv. This is
the beauty of jupiter we can easily visualize our data doing this with vs code and
terminal windows is really tedious and clunky so what is this describe method
returning basically it 's returning some basic information about each column in
this data set. In a real data science or machine learning project we 'll have to
use some techniques to clean up our data set one option is to remove the records
that do n't have a value for the year column.
The first element in our array is an array itself these are the values in this
array which basically represent the first row in our data set so the video game
with ranking 1 which is called wii sports. If we press the escape key green turns
to blue and that means this cell is currently in the command mode. The activated
cell can be either in the edit mode or command mode depending on the mode. When you
run a cell this will only execute the code in that cell. The code in other cells
will not be executed. This notebook file includes our source code organized in
cells as well as the output for each cell. We also have autocompletion and
intellisense so in the cell let 's call df dataframe dot. i just wanted to let you
know that i have an online coding school at cordwindmarch. com where you can find
plenty of courses on web and mobile development in fact i have a comprehensive
python course that teaches you everything about python from the basics to more
advanced concepts. After you watch this tutorial if you want to learn more you may
want to look at my python course it comes with a 30 day money back guarantee and a
certificate of completion.
The second step in a machine learning project is cleaning or preparing the data and
that involves tasks such as removing duplicates null values. again this is a made-
up pattern it 's not the representation of the reality so let 's go ahead and
download this csv file in my downloads folder here we have this music. csv. The
next step is to build a model using a machine learning algorithm. The method takes
two data sets the input set and the output set so they are capital x and y. Finally
we need to ask our model to make a prediction so we can ask it what is the kind of
music that a 21 year old male likes. We 're asking our model to make two
Programming with TANSH_CODES
Machine learning is a subset of artificial intelligence or artificial intelligence.
This tutorial will teach you how to build a model that can learn and predict the
kind of music people like. By the end of this one hour tutorial you will have a
good understanding of machine learning basics. You do n't need any prior knowledge
in machine learning but you need to know python fairly well. Machine learning has
other applications in self-driving cars and robotics language processing vision
processing forecasting things like stock market trends and the weather games and so
on so that 's the basic idea about machine learning next we 'll look at machine
learning in action a machine learning project involves a number of steps the first
step is to import our data which often comes in the form of a csv file. We 're
going to look at the popular python libraries that we use in machine learning
projects the first one is numpy which provides a multi-dimensional array. pandas is
a data analysis library that provides a concept called data frame. matplotlib is a
two-dimensional plotting library for creating graphs and plots. scikit-learn is one
of the most popular machine learning libraries that provides all these common
algorithms like neural networks and neural networks.
Anaconda is that it will install jupyter as well as all those popular data science
libraries like numpy pandas and so on so we do n't have to manually install this
using pip all right now as part of the next step anaconda suggests to install
microsoft vs code we already have this on our machine so we can go with continue
and close the installation. in this notebook we can write python code and execute
it line by line. Kaggle. com is a popular data set that we 're going to use in this
lecture. Create an account you can sign up with facebook google or using a custom
email and password once you sign up then come back here in the search bar search
for video game sales this is the name of a data set called vgsales. csv. This is
the beauty of jupiter we can easily visualize our data doing this with vs code and
terminal windows is really tedious and clunky so what is this describe method
returning basically it 's returning some basic information about each column in
this data set. In a real data science or machine learning project we 'll have to
use some techniques to clean up our data set one option is to remove the records
that do n't have a value for the year column.
The first element in our array is an array itself these are the values in this
array which basically represent the first row in our data set so the video game
with ranking 1 which is called wii sports. If we press the escape key green turns
to blue and that means this cell is currently in the command mode. The activated
cell can be either in the edit mode or command mode depending on the mode. When you
run a cell this will only execute the code in that cell. The code in other cells
will not be executed. This notebook file includes our source code organized in
cells as well as the output for each cell. We also have autocompletion and
intellisense so in the cell let 's call df dataframe dot. i just wanted to let you
know that i have an online coding school at cordwindmarch. com where you can find
plenty of courses on web and mobile development in fact i have a comprehensive
python course that teaches you everything about python from the basics to more
advanced concepts. After you watch this tutorial if you want to learn more you may
want to look at my python course it comes with a 30 day money back guarantee and a
certificate of completion.
The second step in a machine learning project is cleaning or preparing the data and
that involves tasks such as removing duplicates null values. again this is a made-
up pattern it 's not the representation of the reality so let 's go ahead and
download this csv file in my downloads folder here we have this music. csv. The
next step is to build a model using a machine learning algorithm. The method takes
two data sets the input set and the output set so they are capital x and y. Finally
we need to ask our model to make a prediction so we can ask it what is the kind of
music that a 21 year old male likes. We 're asking our model to make two
