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Wondering how to become an expert in the powerful machine and data science technologies? If you want to break into machine learning and data science, the Udemy best-selling course named Machine Learning A-Z™: Hands-On Python & R In Data Science will help you do so. Machine learning and data science are the world’s most popular and talked about skills in tech. We carefully selected the course for you here because it is able to help you become a good data science expert.
Intro to The Machine Learning A-Z Course
In the Machine Learning A-Z™: Hands-On Python & R In Data Science course, you’ll have a depth learning of machine learning algorithms in Python and R programming languages, and thoroughly understand how data science works, and how to become a high-paid data scientist. Once joined the course, you’ll get over 41 hours of HD video guide, 28 articles, 5 downloadable resources, and 291 lectures in total. This will requires a strong willing to get the most out of it. You’ll learn machine learning models, NLP, deep learning, artificial neural networks, convolutionnal neural networks, data science, and more. You’ll work on your own cases like an expert. You’ll be able to start a high-returned career in data science.
Course’s targets and requirements:
The course is designed for anyone who’re willing to join a complete bootcamp and learn all they need to master the machine learning Python, data science, and deep learning. To learn the course only require a high school mathematics level, so don’t miss out on the best machine learning course here. Besides that, the course is a good choice for students, intermediate developers, data analysts, and those people who want to level up in machine learning, data science, reinforcement learning, NLP and more.
What each lecture will teach you:
- 10 lectures will help you understand why machine learning is the future
- 11 lectures on the knowledge of data preprocessing
- 1 lectures on regression
- 12 lectures on the intro to the simple linear regression
- 21 lectures on the intro to multiple linear regression
- 12 lectures on intro to Polynomial regression
- 4 lectures on intro to the support vector regression
- 4 lectures on intro to the decision tree regression in Python and R
- 4 lectures on intro to random forest regression
- 5 lecture on how to master the evaluating regression models performance
- 14 lectures on the skills of the logistic regression in Python
- 4 lectures on intro to K-NN in Python and R programming
- 4 lectures on intro to SVM in Python and R programming
- 7 lectures on intro to the types of Kernel functions, and understand Kernel SVM in Python and R
- 7 lectures on native bayes
- 4 lectures on decision tree classification
- 4 lectures on random forest classification
- 6 lectures on the evaluating classification models performance
- 6 lectures on K-Means clustering
- 15 lectures on hierarchical clustering
- 8 lectures on Apriori
- 3 lectures on eclat
- 11 lectures on upper confidence bound
- 7 lectures on Thompson sampling
- 25 lectures on all the knowledge you need to know about the natural language processing
- 2 lectures on intro to deep learning
- 25 lectures will help you master all you need to know about artificial neural networks
- 22 lectures on intro to convolutional neural networks
- 8 lectures on the principal component analysis
- 4 lectures on linear discriminant analysis
- 3 lectures on kernel PCA
- 6 lectures on model selection
- 5 lectures on XGBoost
- 1 lecture gives you a bonus
Machine Learning Review
In the Machine Learning A-Z™: Hands-On Python & R In Data Science course, you’ll learn to be master in machine learning. In the modern world of technology, we have got several things which have introduced us to ways through which programs can be made even better. They often seem to be out-of-the-future but they are rather the reality that we have right now. Haven’t we all heard about artificial intelligence? Be it in a science fiction show or in a science-based book, it is a thing that amazes us. But machines themselves do not have the ability to learn things themselves. So, it is the humans who have to provide them with the power to learn things and remember them to help other humans. Here we will learn about one such step which allows machines to do so.
What is Machine Learning?
The Machine Learning A-Z™: Hands-On Python & R In Data Science course will help you understand what the machine learning is. Machine Learning is the miraculous and amazing way through which a programmer can provide the ability to a computer to go through data and learn them without them having to program them over and over again. Machine learning enables the computer to use its own intelligence to learn and make the necessary adjustments. It is a way through which development is brought to the usual way in which computers learned things. In 1959 the term was coined by Arthur Samuel, an American pioneer of Artificial Intelligence. Machine learning is a whole process and the computer gets better and better as they get more input. A think about machine learning is that the input and output are both made available for the computer so that they can learn better.
An easy example of Machine learning will be targeted advertisements where a potential customer is bombarded with ads that will be of their interest. People can find it when they are browsing through websites like Facebook and Instagram. Machine learning is also being used for diagnosis where machines can detect cancerous cells easily which can reduce the time taken to diagnosis. To master machine learning, the Udemy best-selling course of Machine Learning A-Z™: Hands-On Python & R In Data Science is a priority.
Methods Used in Machine Learning:
Machine Learning is a progressive field and something new comes up almost every day. Right now, there are a few ways through which machine learning can be utilized on a computer. So, let us know a bit more about some of them:
Supervised machine learning: This is the method in which the algorithms help the machines to learn examples from before and also lets them look at the responses. This, in turn, helps the machines to predict outcomes when they are given similar inputs. This is quite similar to the way in which human learns under their teacher who teaches them with the help of examples and lets them know about the desirable outcomes.
Unsupervised machine learning: In this method, the algorithms that are utilized for teaching the machine do not fall in any particular class or they lack labels. The machines aren’t given any sort of probable outcome for an example. Rather than predicting outcomes, this method of machine learning helps the machine to classify the data or find patterns or correlations that can be hidden in the data given to it. This kind of machine learning is generally used in marketing automation.
Reinforcement learning: The simplest way to define reinforcement learning is by saying that it is a train and error method. You can learn more about it from the Machine Learning A-Z™: Hands-On Python & R In Data Science course. Whenever the algorithm is fed to the machine along with the un-categorized data there is a possibility of a negative or a positive outcome. So, the machine they will need to learn the best and the easiest way to get a positive outcome. The outcome that the machine will come up with will be prescriptive in nature. The errors that come along the way of learning help the machine to learn better.
Semi-supervised machine learning: By the very name you can understand that the algorithms utilized in this method of machine learning are a somewhat in-between supervised and unsupervised machine. In this method, both unlabeled and labeled data are utilized together. The amount of unlabeled data is more than that of labeled data. It is a way through which skilled and relevant outcomes can be acquired for the labeled data to learn with the help of it.
Benefits of Using Machine Learning:
If you are going to use Machine Learning, then it is better to learn more about the advantages of it. In the Machine Learning A-Z™: Hands-On Python & R In Data Science course, you’ll know more about it. Here are them:
- Machine learning is one of the best ways to identify trends and patterns present in a data set that has been given to a computer. These patterns are important right now as they help the market to grow by knowing about each and every person and their interests.
- Machine learning works on automation once the algorithm has been set. So, a person wouldn’t really need to interfere over and over again to get the desired result out of the computer. Also, machine learning is the way through which the computer or machine gets to learn new things and improve themselves. The outcomes get better and accurate as it learns new things.
- Machine learning provides real-time predictions for which a person doesn’t need to wait for an eternity. Once the algorithm is fed, the computer will be able to process the data in no time and provide the outcome through the method that has been utilized by the program.
- Humans cannot handle a lot of data which are multi-dimensional in nature. If you want to have an analysis report or outcome, then you will need to wait and often there will be a need to divide the work between people. But this doesn’t apply when you are using machine learning which has the ability to handle multi-dimensional data as well as multi-variety in data.
- Machine learning can be used in a variety of sectors and currently it is one of the most used tools in case of the business industry. Machine learning is the way through which one can know about their customers and it can predict the needs and wants of them. It is also deeply important in the health sector. We will learn more about it later.
Sectors Where Machine Learning is Used:
When we think about Machine Learning we have to regard the fact that it has a worldwide presence as of now. If you are soaring to be a programmer who is specializing in Artificial Intelligence, then you will need to learn about Machine learning.And the Machine Learning A-Z™: Hands-On Python & R In Data Science course is highly recommended. As customer satisfaction is rising so is the need to have better machine learning so that AI can improve. So, here are some of the sectors where you can usually see the presence of Machine learning:
Finance sector: As people are progressing so is their need for having better banking solutions. The advent of digital currency and the utilization of technology for transactions call in the need for artificial intelligence. In banking, machine learning can help in detecting frauds to warn the company as well as the client. Also, it is a way in which the predictions of the share market can get better even without human intervention.
Health Care sector: These days’ humans are living a long life than at any time before. So, if we use Machine learning in the healthcare sector, it can greatly improve diagnosis and also help to treat diseases better. This is especially important for critical and life-threatening diseases.
Oil and Gas sector: One of the most important resources that we need are fossil fuels. In this sector machine learning is widely used to know about the patterns and also about the flow present in the industry. People are constantly trying to make progress in this field.
Government sector: A citizen of a country needs to have the best government so that they can have a life which is free from problems. In turn, a government needs to know more about its citizens. Machine learning does help the government to analyze and predict from the data that they have with themselves. This, in turn, helps to increase the efficiency of the government so that they can work better. Machine learning is also the way through which governments can battle frauds and intrusions. So, time to learn the powerful machine learning technology? Don’t forget to join the Machine Learning A-Z™: Hands-On Python & R In Data Science course at Udemy.
Business sector: The business sector loves Machine learning. It has provided them the path to pursue targeted advertisements that can increase their sales. This is used for everything from selling a beauty product to selling health insurance to a person. A company often utilizes machine learning to produce an AI which can give them the right predictions and outcomes by analysing the data that they have collected. If you see a book that you like in the recommendation section of Amazon, then it is the work of machine learning.
Transportation sector: This is an important sector as there is always a need to get things from one place to another. Machine learning is used to detect patterns and to predict the best ways to transport along with probable problems. The self-driving car also makes use of machine learning which predicts the best route that one can take to reach their destination. Delivery companies often use machine learning to optimize and fasten each process.
So, here is the most basic way through which we can introduce Machine Learning to you, you can know more about by learning the Machine Learning A-Z™: Hands-On Python & R In Data Science course. Anyone who is interested in learning more about Artificial intelligence will need to go through the process of machine learning. Do try to learn from the best place available and it may provide you with a nice career!
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