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This tutorial’s code is available on Github and its full implementation as well on Google Colab
The foundation of machine learning and deep learning systems wholly base upon mathematics principles and concepts. It is imperative to understand the fundamental foundations of mathematical principles. During the baseline and building of the model, many mathematical concepts like the curse of dimensionality, regularization, binary, multi-class, ordinal regression, and others must be artistic in mind.
The basic unit of deep learning, commonly called a neuron, is wholly based on its mathematical concept, and such involves the sum of the multiplied values involving input and weight. Its activation functions like Sigmoid, ReLU, and others, have been built using mathematical theorems.
These are the essential mathematical areas to understand the basic concepts of machine learning and deep learning appropriately:
#linear-algebra #deep-learning #machine-learning #mathematics
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When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.
When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,
#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services
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Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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Description
Become a Python Programmer and learn one of employer’s most requested skills of 21st century!
This is the most comprehensive, yet straight-forward, course for the Python programming language on Simpliv! Whether you have never programmed before, already know basic syntax, or want to learn about the advanced features of Python, this course is for you! In this course we will teach you Python 3. (Note, we also provide older Python 2 notes in case you need them)
With over 40 lectures and more than 3 hours of video this comprehensive course leaves no stone unturned! This course includes tests, and homework assignments as well as 3 major projects to create a Python project portfolio!
This course will teach you Python in a practical manner, with every lecture comes a full coding screencast and a corresponding code notebook! Learn in whatever manner is best for you!
We will start by helping you get Python installed on your computer, regardless of your operating system, whether its Linux, MacOS, or Windows, we’ve got you covered!
We cover a wide variety of topics, including:
Command Line Basics
Installing Python
Running Python Code
Strings
Lists
Dictionaries
Tuples
Sets
Number Data Types
Print Formatting
Functions
Scope
Built-in Functions
Debugging and Error Handling
Modules
External Modules
Object Oriented Programming
Inheritance
Polymorphism
File I/O
Web scrapping
Database Connection
Email sending
and much more!
Project that we will complete:
Guess the number
Guess the word using speech recognition
Love Calculator
google search in python
Image download from a link
Click and save image using openCV
Ludo game dice simulator
open wikipedia on command prompt
Password generator
QR code reader and generator
You will get lifetime access to over 40 lectures.
So what are you waiting for? Learn Python in a way that will advance your career and increase your knowledge, all in a fun and practical way!
Basic knowledge
Basic programming concept in any language will help but not require to attend this tutorial
What will you learn
Learn to use Python professionally, learning both Python 2 and Python 3!
Create games with Python, like Tic Tac Toe and Blackjack!
Learn advanced Python features, like the collections module and how to work with timestamps!
Learn to use Object Oriented Programming with classes!
Understand complex topics, like decorators.
Understand how to use both the pycharm and create .py files
Get an understanding of how to create GUIs in the pycharm!
Build a complete understanding of Python from the ground up!
#Learn Python #Learn Python from Basic #Python from Basic to Advance #Python from Basic to Advance with Projects #Learn Python from Basic to Advance with Projects in a day
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If you want to become a machine learning professional, you’d have to gain experience using its technologies. The best way to do so is by completing projects. That’s why in this article, we’re sharing multiple machine learning projects in Python so you can quickly start testing your skills and gain valuable experience.
However, before you begin, make sure that you’re familiar with machine learning and its algorithm. If you haven’t worked on a project before, don’t worry because we have also shared a detailed tutorial on one project:
#artificial intelligence #machine learning #machine learning in python #machine learning projects #machine learning projects in python #python
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If you want to become a machine learning professional, you’d have to gain experience using its technologies. The best way to do so is by completing projects. That’s why in this article, we’re sharing multiple machine learning projects in Python so you can quickly start testing your skills and gain valuable experience.
However, before you begin, make sure that you’re familiar with machine learning and its algorithm. If you haven’t worked on a project before, don’t worry because we have also shared a detailed tutorial on one project:
The Iris dataset is easily one of the most popular machine learning projects in Python. It is relatively small, but its simplicity and compact size make it perfect for beginners. If you haven’t worked on any machine learning projects in Python, you should start with it. The Iris dataset is a collection of flower sepal and petal sizes of the flower Iris. It has three classes, with 50 instances in every one of them.
We’ve provided sample code on various places, but you should only use it to understand how it works. Implementing the code without understanding it would fail the premise of doing the project. So be sure to understand the code well before implementing it.
#artificial intelligence #machine learning #machine learning in python #machine learning projects #machine learning projects in python #python