You’ll receive the completely annotated Jupyter Notebook used in the course.
You’ll be able to define and give examples of the top libraries in Python used to build real world predictive models.
You will be able to create models with the most powerful language for machine learning there is.
You’ll understand the supervised predictive modeling process and learn the core vernacular at a high level.
Requirements
There are no prerequisites however knowledge of Python will be helpful.
A familiarity with the concepts of machine learning would be helpful but aren’t necessary.
Description
Recent Review from Similar Course:
“This was one of the most useful classes I have taken in a long time. Very specific, real-world examples. It covered several instances of ‘what is happening’, ‘what it means’ and ‘how you fix it’. I was impressed.” Steve
Welcome to The Top 5 Machine Learning Libraries in Python. This is an introductory course on the process of building supervised machine learning models and then using libraries in a computer programming language called Python.
What’s the top career in the world? Doctor? Lawyer? Teacher? Nope. None of those.
The top career in the world is the data scientist. Great. What’s a data scientist?
The area of study which involves extracting knowledge from data is called Data Science and people practicing in this field are called as Data Scientists.
Business generate a huge amount of data. The data has tremendous value but there so much of it where do you begin to look for value that is actionable? That’s where the data scientist comes in. The job of the data scientist is to create predictive models that can find hidden patterns in data that will give the business a competitive advantage in their space.
Don’t I need a PhD? Nope. Some data scientists do have PhDs but it’s not a requirement. A similar career to that of the data scientist is the machine learning engineer.
A machine learning engineer is a person who builds predictive models, scores them and then puts them into production so that others in the company can consume or use their model. They are usually skilled programmers that have a solid background in data mining or other data related professions and they have learned predictive modeling.
In the course we are going to take a look at what machine learning engineers do. We are going to learn about the process of building supervised predictive models and build several using the most widely used programming language for machine learning. Python. There are literally hundreds of libraries we can import into Python that are machine learning related.
A library is simply a group of code that lives outside the core language. We “import it” into our work space when we need to use its functionality. We can mix and match these libraries like Lego blocks.
Thanks for your interest in the The Top 5 Machine Learning Libraries in Python and we will see you in the course.
Who this course is for:
If you’re looking to learn machine learning then this course is for you.
There are no requirements or prerequisites for this course
Description
This course is designed for all python developers who are eager to learn different features and functions of Jupyter notebook. This course will provide you complete knowledge and understanding of frequently used Jupyter notebook features. With the help of this course, your productivity and coding skills will reach the next level.
This course is for all the developers from beginners to advance, if you are a new Python developer or an experienced one, you will definitely learn something new in this course.
We’ll start our course with an introduction to Anaconda and Jupyter notebook. After the introduction, Anaconda installation will be performed and I will show you how to start writing code in Jupyter Notebook. Our next step will be to go through Menu tabs and all options inside each tab to get familiar with their functions. We’ll also look at Cell types, Modes, Shortcuts and Magic Commands. At the end we’ll see how can we publish the Jupyter notebook file on a website or blog and how can we share it with other team members.
Have completed Survival Python or have equivalent Python experience
You will need to be able to install software on your machine
The Anaconda distro of Python
Description
You know Python. You know Excel. You may even know how to crunch numbers in R using the Tidyverse if you have a statistics background.
But when it comes to applying all this knowledge to the world of data science, you know you need more than these tools to be successful. What makes matters worse is that you are not exactly sure of what order you should be learning which data science tools. It can be a challenge to know exactly where to focus, and how to apply what you do know.
At Mass Street University, we guide statisticians and developers interested in exploring how to process and analyze data—efficiently. In Python for Data Analysis, we focus you on precisely what you need to know, and teach you how best to utilize what you already do know.
In the course, we will teach you how to combine your existing knowledge of Python with tools like Pandas and Numpy. If you have only worked with the basic Python data types, approaching some of the higher order data types can be intimidating. The structure of our course takes you from the simplest tools to the more complex to ensure you stay focused on what you need while you build on your font of data science knowledge.
JupyterLab is one tool you may not be familiar with, and it is a popular data analysis notebook that supports many languages, including Python. Notebook technology is relatively new to the world of data science, and we will go over how JupyterLab will allow you to write much smaller amounts of code efficiently.
There are a ton of data science tools that interact very well with Python to make data science a breeze when explored and taught properly. And at Mass Street University, we make sure that this dynamic is managed as efficiently as possible. Enroll today in Python for Data Analysis to stay focused on what you need to excel in data analysis.
Who this course is for:
Students who have just finished Survival Python.
Developers who are familiar with Python but have never worked in data science and want to learn the most commonly used tools.
Statisticians looking to migrate from R to Python.
Python is the fastest growing Data Analytics Programming Languages. This course provides you with foundational knowledge of Python and introduces you to analyzing data using Python.
Knowing Python is highly important if you intend working with data and the demand for professionals with Python skills is ever growing.
You will learn Python in a practical way using Jupyter notebook.
You will work on a guided project that you can share with family and friends using all the topics covered in this course
This course is hands-on with practice tasks which allows you get comfortable and familiar with coding in Python.
Content of This Course Includes:
Python as a Programming Language, Data Types, Variables, Operators, Numbers in Python, String Data Type, String Methods, Slicing, Functions, Casting Variables.
You will also learn about what you need to get into a data related career.
Course Requirement or Prerequisites
This course does not require any prior knowledge or specific academic background. The only requirement is having a laptop or desktop computer. All applications necessary for learning the course would be downloaded free from the internet.
Who is this course for?
Anyone looking to work with data personally or professionally.
Looking into a career as Data Analyst, Data Scientist, Business Analyst, Report Analyst, ETL Specialist, BI Consultant, Data Engineer or any Data related field.
Who this course is for:
Anyone who wants to learn Python from the beginning to becoming highly proficient.
Looking into a career in any data related field – Data Scientist, Data Analyst, Business Analyst, Database Administration, BI Analyst, Artificial Intelligence e.t.c.
Get started with Computer Vision using OpenCV, the largest and most extensive Computer Vision library in the world!
Requirements
Basic Knowledge of Python
Description
Learn to use OpenCV for Computer Vision and AI in this official course for absolute beginners from OpenCV. You will learn and get exposed to a wide range of exciting topics like Image & Video Manipulation, Image Enhancement, Filtering, Edge Detection, Object Detection and Tracking, Face Detection, and the OpenCV Deep Learning Module.
This course helps you confidently take your very first steps in the exciting world of Computer Vision and AI. This field offers limitless opportunities in the Computer Vision and AI job market. Embark on this learning journey and welcome to the AI revolution!
Course Contents
Module 1: Getting Started with Images
Module 2: Basic Image Manipulation
Module 3: Image Annotation
Module 4: Arithmetic Operations on Images
Module 5: Bitwise Operations on Images
Module 6: Accessing the Camera
Module 7: Read and Write Videos
Module 8: Image Filtering and Edge Detection
Module 9: Image Features and Image Alignment
Module 10: Image Stitching and Creating Panoramas
Module 11: Object Tracking in OpenCV
Module 12: Face Detection using Deep Learning
Module 13: Object Detection using Deep Learning
Module 14: Pose Estimation using OpenPose
Course Features
Designed By Industry Experts: This course in OpenCV and Python is for absolute beginners has been designed by our team of engineers and researchers, currently working in the field of Computer Vision and Deep Learning. This course will help you confidently take your very first steps into the exciting world of Computer Vision and AI.
Powered By Python: The programming language of choice for this short introductory course is Python, one of the most comprehensive and widely used languages in AI.
Foundational & Experiential Learning: This course will help you develop a broad and basic understanding and practice of the subject matter before committing to more structured formal learning paths from beginner to mastery levels that are available online through OpenCV.
Practical & Intuitive: The field of Computer Vision contains many theoretical underpinnings which can become a stumbling block for absolute beginners, especially, when courses contain heavy mathematics. With this in mind, we have created this ‘getting started’ course to provide you a wide exposure to this exciting field.
Who this course is for:
Beginner Python Developers eager to learn Computer Vision and Deep Learning
Once you have the basics of programming down and are able to write programs little by little, you will have the desire to “automate various things! I want to automate a lot of things! That was the case with me.
PyAutoGUI” is one of the libraries to power up Python. Specifically, it is a library that allows you to programmatically execute keyboard and mouse operations.
If keyboard and mouse operations can be automated, what can you do?
If you have a large number of the same repetitive tasks, automate them and you will never have to operate a computer again. You can have a cup of coffee or read a book while you work. Run it before you go to bed and it will do the work while you sleep. Automation gives you more time.
I’m a little late, but I’d like to introduce myself. After working as a guitar and furniture maker, I became independent. Currently, I manufacture and manage original brands and OEM production. I have also been studying IT before becoming independent. I am a producer, IT person, and manager.
Environment construction is not explained.
Please have pyautogui and time available.
Use jupyter notebook.
The operation screen of Mac is recorded.
Windows users, please set command to ctrl and option to alt.
I create my courses in the form of scripted reading. I also cut out as much silence as possible. Please be aware that it may sound monotonous. If you feel that the speed of speech is too fast or too slow, please use Udemy’s speed adjustment to make it easier for you to learn. So let’s get started together!
Learn how to become Python Professional Programmer for FREE and get yourself hired!
Requirements
No experience needed because the course start with the basic introduction
No programming skills required to master this course
Only computer/tablet/phone and internet
You don’t need to install any Python software to follow this course and learn Python
Description
In this course you will learn everything about Python programming language. We will start with the basic syntax and we will move to learn more complex concepts like data types, type conversion, data structures like lists, dictionaries, tuples and sets where you can store more data in organised manner. The Python programming language is very easy language to learn if you have the right course or the right guide. With this course I will explain everything you need to know in simple English. This means you will be able to understand even the hard concepts without any problems.
Here are some of the things we will cover:
Tools we can use to run Python Code
Basic Python Syntax
Python Data Types like Integer, Floats, Strings, Lists, Tuples, Sets and Dictionaries
Formatted Strings & How Strings are Stored in Memory
Escape Characters
String Slicing
Functions and Methods (built-in Python Functions)
Python IN Keyword
Control Structures If, if-else, elif
Python Indentation
Operators, Logical and Comparison Operators
Loops in Python – For loop
Python Nested loops (for-loops)
While loops
*args, **kwargs
Installing Python locally
OOP ( Object Oriented Programming) Classes and Objects
If you have learned any previous programming language then learning Python will be very easy process but everyone can learn it even the absolute beginners because I will start from the very basics.
What are you still waiting for, click on the enrol button and see me on the other side 🙂
Rick
Who this course is for:
Everyone that wants to learn Python programming
Beginner Python developers that wants to learn Python Programming from scratch
Everyone that wants to learn and build strong understanding of python
Even teachers and tutor can use this course to pass the knowledge to their students
Even professional programmers can go over this course and refresh their memories
Learn & Increase your Python skills & logical thinking in just 2 hours with this project oriented weekend course.
Requirements
Basic knowledge of Python Programming language
Description
Increase your python Knowledge by practicing Real life projects based on python and learn more by Practice activities given in this course.
In this course you will get to learn about :
Some wonderful python projects that will strengthen your CV
how to develop new project ideas in python programming language
how to implement new project ideas on your own using Python.
Some best libraries of python like time, playsound, Tkinter etc.
Logic building ability for making projects in Python
Some new concepts of python programming language
Build fun and memorable projects
Learn how to code in Python in simple and easy way.
Learn Python Functions Programming.
CREATE your own Programs and Applications using python.
Graphical User Interface (GUI) in Python
Errors and Exceptions Handling
Be able to use the in-built Python modules for their own projects
Build Python Graphical User Interfaces(GUI) with Tkinter
Build simple Python based games using programming loops and functions
Get a handle on working with Python 3
Working with text editors like Jupyter Notebook.
Be able to program in Python professionally
Build GUIs and Desktop applications with Python
In this course you will learn to make different python projects, which help you to learn “How to put theory into practice and How to think computationally Problem solving with Python with help of numerous exercises.”
Projects are basically named as:
Number Guessing GameIn this project we create a script, which will ask the user to guess a number between 1 and 100.Best part is user has only 5 guesses to guess the number which make this game more interesting.We are using the random module with the randrange() function to get a random number.
In this project you will learn about random module, time module and its functions, while loop, if elif statement and more.
Tic-Tac-ToeTic-Tac-Toe is a very simple two-player game. So only two players can play at a time. This game is also known as Noughts and Crosses or Xs and Os game. One player plays with X and the other player plays with O. In this game we have a board consisting of a 3X3 grid. In this project we create a script which help us to play this game.
In this project you will learn about Python dictionary, creating function and function calling , list, string string concatenation, for loop, if elif statement and more.
Who this course is for:
Beginner and Intermediate python developer who wants to increase the python knowledge.
