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Python Programming: Machine Learning, Deep Learning | Python
Last updated 4/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English (US) | Size: 2.82 GB | Duration: 21h 15m

Python Machine Learning and Python Deep Learning with Data Analysis, Artificial Intelligence, OOP, and Python Projects

What you'll learn
Fundamental stuff of Python and its library Numpy
What is the AI, Machine Learning and Deep Learning
History of Machine Learning and python programming
Turing Machine and Turing Test
The Logic of Machine Learning such as Machine Learning models and algorithms, Gathering data, Data pre-processing, Training and testing the model etc.
What is Artificial Neural Network (ANN)
Anatomy of NN
Tensor Operations
Python instructors on Udemy specialize in everything from software development to data analysis, and are known for their effective.
Machine learning isn't just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries.
The Engine of NN
Keras
Tensorflow with python programming
Convolutional Neural Network
Recurrent Neural Network and LTSM
Transfer Learning with python programming
Python instructors on Udemy specialize in everything from software development to data analysis, and are known for their effective.
Python (python programming)
Machine Learning, python machine learning
Deep Learning, python deep learning
Machine Learning with Python
Python Programming
Deep Learning with Python
Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective.
Python is a general-purpose, object-oriented, high-level programming language.
Python is a multi-paradigm language, which means that it supports many programming approaches. Along with procedural and functional programming styles
Python is a widely used, general-purpose programming language, but it has some limitations. Because Python is an interpreted, dynamically typed language
Python is a general programming language used widely across many industries and platforms. One common use of Python is scripting, which means automating tasks.
Python is a popular language that is used across many industries and in many programming disciplines. DevOps engineers use Python to script website.
Python has a simple syntax that makes it an excellent programming language for a beginner to learn. To learn Python on your own, you first must become familiar
Machine learning describes systems that make predictions using a model trained on real-world data.
Machine learning is being applied to virtually every field today. That includes medical diagnoses, facial recognition, weather forecasts, image processing.
It's possible to use machine learning without coding, but building new systems generally requires code.
Python is the most used language in machine learning. Engineers writing machine learning systems often use Jupyter Notebooks and Python together.
Machine learning is generally divided between supervised machine learning and unsupervised machine learning. In supervised machine learning.
Machine learning is one of the fastest-growing and popular computer science careers today. Constantly growing and evolving.
Machine learning is a smaller subset of the broader spectrum of artificial intelligence. While artificial intelligence describes any "intelligent machine"
A machine learning engineer will need to be an extremely competent programmer with in-depth knowledge of computer science, mathematics, data science.
Python Machine Learning and Python Deep Learning with Data Analysis, Artificial Intelligence, OOP, and Python Projects

Requirements
Python Coding skills are a plus
Math skills will boost your understanding
Be able to download and install all the free software and tools needed to practice
A strong work ethic, willingness to learn and plenty of excitement about the back door of the digital world
Just you, your computer and your ambition to get started now!
Basic knowledge of Python Programming Language
Free software and tools used during the machine learning a-z course
Determination to learn machine learning and patience.
Curiosity for machine learning python
Desire to learn Python
Desire to work on python machine learning
Desire to learn Python 3
Desire to learn numpy
Desire to learn numpy python, machine learning, deep learning
Desire to learn artificial intelligence with python, numpy python, python deep learning, python machine learning

Description
Hello there,Welcome to the "Python Programming: Machine Learning, Deep Learning | Python" coursePython, machine learning, python programming, django, ethical hacking, data analysis, python for beginners, machine learning python, python bootcampPython Machine Learning and Python Deep Learning with Data Analysis, Artificial Intelligence, OOP, and Python ProjectsComplete hands-on deep learning tutorial with Python Learn Machine Learning Python, go from zero to hero in Python 3Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels Whether you work in machine learning or finance, or are pursuing a career in web development or data science, Python is one of the most important skills you can learn Python's simple syntax is especially suited for desktop, web, and business applications Python's design philosophy emphasizes readability and usability Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization The core programming language is quite small and the standard library is also large In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks Machine learning isn't just useful for predictive texting or smartphone voice recognition Machine learning is constantly being applied to new industries and new problems Whether you're a marketer, video game designer, or programmer, this course is here to help you apply machine learning to your work It's hard to imagine our lives without machine learning Predictive texting, email filtering, and virtual personal assistants like Amazon's Alexa and the iPhone's Siri, are all technologies that function based on machine learning algorithms and mathematical models Python programming: machine learning deep learning | python, python programming: machine learning deep learning, machine learning python, deep learning, machine learning, deep learning python, python programming machine learning deep learning, python programming machine learning, oak academy, pythonIn this course, we will learn what is Deep Learning and how does it workThis course has suitable for everybody who interested in Machine Learning and Deep Learning concepts in Data ScienceFirst of all, in this course, we will learn some fundamental stuff of Python and the Numpy library These are our first steps in our Deep Learning journey After then we take a little trip to Machine Learning Python history Then we will arrive at our next stop Machine Learning in Python Programming Here we learn the machine learning concepts, machine learning a-z workflow, models and algorithms, and what is neural network concept After then we arrive at our next stop Artificial Neural network And now our journey becomes an adventure In this adventure we'll enter the Keras world then we exit the Tensorflow world Then we'll try to understand the Convolutional Neural Network concept But our journey won't be over Then we will arrive at Recurrent Neural Network and LTSM We'll take a look at them After a while, we'll trip to the Transfer Learning concept And then we arrive at our final destination Projects in Python Bootcamp Our play garden Here we'll make some interesting machine learning models with the information we've learned along our journeyIn this course, we will start from the very beginning and go all the way to the end of "Deep Learning" with examplesThe Logic of Machine Learning such as Machine Learning models and algorithms, Gathering data, Data pre-processing, Training and testing the model etcBefore we start this course, we will learn which environments we can be used for developing deep learning projectsDuring the course you will learn:Fundamental stuff of Python and its library NumpyWhat is the Artificial Intelligence (Ai), Machine Learning, and Deep LearningHistory of Machine LearningTuring Machine and Turing TestThe Logic of Machine Learning such asUnderstanding the machine learning modelsMachine Learning models and algorithmsGathering dataData pre-processingChoosing the right algorithm and modelTraining and testing the modelEvaluationArtificial Neural Network with these topicsWhat is ANNAnatomy of NNTensor OperationsThe Engine of NNKerasTensorflowConvolutional Neural NetworkRecurrent Neural Network and LTSMTransfer LearningReinforcement LearningFinally, we will make four different projects to reinforce what we have learned What is machine learning?Machine learning describes systems that make predictions using a model trained on real-world data For example, let's say we want to build a system that can identify if a cat is in a picture We first assemble many pictures to train our machine learning model During this training phase, we feed pictures into the model, along with information around whether they contain a cat While training, the model learns patterns in the images that are the most closely associated with cats This model can then use the patterns learned during training to predict whether the new images that it's fed contain a cat In this particular example, we might use a neural network to learn these patterns, but machine learning can be much simpler than that Even fitting a line to a set of observed data points, and using that line to make new predictions, counts as a machine learning model What is machine learning used for?Machine learning a-z is being applied to virtually every field today That includes medical diagnoses, facial recognition, weather forecasts, image processing, and more In any situation in which pattern recognition, prediction, and analysis are critical, machine learning can be of use Machine learning is often a disruptive technology when applied to new industries and niches Machine learning engineers can find new ways to apply machine learning technology to optimize and automate existing processes With the right data, you can use machine learning technology to identify extremely complex patterns and yield highly accurate predictions Does Machine learning require coding?It's possible to use machine learning data science without coding, but building new systems generally requires code For example, Amazon's Rekognition service allows you to upload an image via a web browser, which then identifies objects in the image This uses a pre-trained model, with no coding required However, developing machine learning systems involves writing some Python code to train, tune, and deploy your models It's hard to avoid writing code to pre-process the data feeding into your model Most of the work done by a machine learning practitioner involves cleaning the data used to train the machine They also perform "feature engineering" to find what data to use and how to prepare it for use in a machine learning model Tools like AutoML and SageMaker automate the tuning of models Often only a few lines of code can train a model and make predictions from itWhat is the best language for machine learning?Python is the most used language in machine learning using python Engineers writing machine learning systems often use Jupyter Notebooks and Python together Jupyter Notebooks is a web application that allows experimentation by creating and sharing documents that contain live code, equations, and more Machine learning involves trial and error to see which hyperparameters and feature engineering choices work best It's useful to have a development environment such as Python so that you don't need to compile and package code before running it each time Python is not the only language choice for machine learning Tensorflow is a popular framework for developing neural networks and offers a C++ API There is a complete machine learning framework for C# called ML NET Scala or Java are sometimes used with Apache Spark to build machine learning systems that ingest massive data sets What are the different types of machine learning?Machine learning is generally divided between supervised machine learning and unsupervised machine learning In supervised machine learning, we train machine learning models on labeled data For example, an algorithm meant to detect spam might ingest thousands of email addresses labeled 'spam' or 'not spam ' That trained model could then identify new spam emails even from data it's never seen In unsupervised learning, a machine learning model looks for patterns in unstructured data One type of unsupervised learning is clustering In this example, a model could identify similar movies by studying their scripts or cast, then group the movies together into genres This unsupervised model was not trained to know which genre a movie belongs to Rather, it learned the genres by studying the attributes of the movies themselves There are many techniques available within Is Machine learning a good career?Machine learning python is one of the fastest-growing and popular computer science careers today Constantly growing and evolving, you can apply machine learning to a variety of industries, from shipping and fulfillment to medical sciences Machine learning engineers work to create artificial intelligence that can better identify patterns and solve problems The machine learning discipline frequently deals with cutting-edge, disruptive technologies However, because it has become a popular career choice, it can also be competitive Aspiring machine learning engineers can differentiate themselves from the competition through certifications, boot camps, code repository submissions, and hands-on experience What is the difference between machine learning and artifical intelligence?Machine learning is a smaller subset of the broader spectrum of artificial intelligence While artificial intelligence describes any "intelligent machine" that can derive information and make decisions, machine learning describes a method by which it can do so Through machine learning, applications can derive knowledge without the user explicitly giving out the information This is one of the first and early steps toward "true artificial intelligence" and is extremely useful for numerous practical applications In machine learning applications, an AI is fed sets of information It learns from these sets of information about what to expect and what to predict But it still has limitations A machine learning engineer must ensure that the AI is fed the right information and can use its logic to analyze that information correctly What skills should a machine learning engineer know?A python machine learning engineer will need to be an extremely competent programmer with in-depth knowledge of computer science, mathematics, data science, and artificial intelligence theory Machine learning engineers must be able to dig deep into complex applications and their programming As with other disciplines, there are entry-level machine learning engineers and machine learning engineers with high-level expertise Python and R are two of the most popular languages within the machine learning field What is python?Machine learning python is a general-purpose, object-oriented, high-level programming language Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python bootcamp is one of the most important skills you can learn Python's simple syntax is especially suited for desktop, web, and business applications Python's design philosophy emphasizes readability and usability Python was developed on the premise that there should be only one way (and preferab

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