Kaggle Master with Heart Attack Prediction Kaggle Project
Kaggle is Machine Learning & Data Science community. Become Kaggle master with real machine learning kaggle project
Desire to learn about Kaggle
Watch the course videos completely and in order
Any device such as mobile phone, computer, or tablet where you can watch the lesson.
Learning determination and patience.
LIFETIME ACCESS, course updates, new content, anytime, anywhere, on any device
Nothing else! It’s just you, your computer and your ambition to get started today
Desire to improve Data Science, Machine Learning, Python Portfolio with Kaggle
Free software and tools used during the course
Description Kaggle, machine learning, data science, python, statistics, r, machine learning python, python data science, deep learning, python programming, django, machine learning a-z, data scientist, python for data science Hello there, Welcome to the “ Kaggle Masterclass with Hearth Attack Prediction Project ” course. Kaggle is Machine Learning & Data Science community. Boost your CV with Hearth Attack Prediction Project in Kaggle Kaggle, a subsidiary of Google LLC, is an online community of data scientists and machine learning practitioners. Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges. Kaggle offers a no-setup, customizable, Jupyter Notebooks environment. Access free GPUs and a huge repository of community-published data & code. Kaggle is a platform where data scientists can compete in machine learning challenges. These challenges can be anything from predicting housing prices to detecting cancer cells. Kaggle has a massive community of data scientists who are always willing to help others with their data science problems. In addition to the competitions, Kaggle also has many tutorials and resources that can help you get started in machine learning. 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, Oak Academy has a course 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. 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. A machine learning course teaches you the technology and concepts behind predictive text, virtual assistants, and artificial intelligence. You can develop the foundational skills you need to advance to building neural networks and creating more complex functions through the Python and R programming languages. Machine learning training helps you stay ahead of new trends, technologies, and applications in this field. We have more data than ever before. But data alone cannot tell us much about the world around us. We need to interpret the information and discover hidden patterns. This is where data science comes in. Data science uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction. Data science seeks to find patterns in data and use those patterns to predict future data. It draws on machine learning to process large amounts of data, discover patterns, and predict trends. Data science includes preparing, analyzing, and processing data. It draws from many scientific fields, and as a science, it progresses by creating new algorithms to analyze data and validate current methods. Data science application is an in-demand skill in many industries worldwide — including finance, transportation, education, manufacturing, human resources, and banking. Explore data science courses with Python, statistics, machine learning, and more to grow your knowledge. Get data science training if you’re into research, statistics, and analytics. If you are an aspiring data scientist, Kaggle is the best way to get started. Many companies will give offers to those who rank highly in their competitions. In fact, Kaggle may become your full-time job if you can hit one of their high rankings. Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 50,000 public datasets and 400,000 public notebooks to conquer any analysis in no time. Do you know that there is no such detailed course on Kaggle on any platform? And do you know data science needs will create 11.5 million job openings by 2026? Do you know the average salary is $100.000 for data science careers! DATA SCIENCE CAREERS ARE SHAPING THE FUTURE AND SO REVIEVE THIS CAREER WITH THE KAGGLE PLATFORM Well, why is Data Science such an important field? Let's examine it together. Data science experts are needed in almost every field, from government security to dating apps. Millions of businesses and government departments rely on big data to succeed and better serve their customers. So, data science careers are in high demand.
If you want to learn one of the employer’s most requested skills?
If you are curious about Data Science and looking to start your self-learning journey into the world of data with Python?
If you are an experienced developer and looking for a landing in Data Science!
In all cases, you are at the right place! We've designed for you “Kaggle - Get The Best Data Science, Machine Learning Profile” a super course to improve your CV in data science. In the course, you will study each chapter in detail. With this course, you will get to know the Kaggle platform step by step. This course is for everyone! My “Kaggle Masterclass with Hearth Attack Prediction Project” is for everyone! If you don’t have any previous experience, not a problem! This course is expertly designed to teach everyone from complete beginners, right through to professionals (as a refresher). What will you learn? In this course, we will start from the very beginning and go all the way to end of "Kaggle" with examples. During the course you will see the following topics:
What is Kaggle?
Registering on Kaggle and Member Login Procedures
Getting to Know the Kaggle Homepage
Competitions on Kaggle
Datasets on Kaggle
Examining the Code Section in Kaggle
What is Discussion on Kaggle?
Courses in Kaggle
Ranking Among Users on Kaggle
Blog and Documentation Sections
User Page Review on Kaggle
Treasure in The Kaggle
Publishing Notebooks on Kaggle
What Should Be Done to Achieve Success in Kaggle?
Recognizing Variables In Dataset
Required Python Libraries
Loading the Dataset
Initial analysis on the dataset
Examining Missing Values
Examining Unique Values
Separating variables (Numeric or Categorical)
Examining Statistics of Variables
Numeric Variables (Analysis with Distplot)
Categoric Variables (Analysis with Pie Chart)
Examining the Missing Data According to the Analysis Result
Numeric Variables – Target Variable
Examining Numeric Variables Among Themselves
Feature Scaling with the Robust Scaler Method
Creating a New DataFrame with the Melt() Function
Numerical - Categorical Variables
Preparation for Modelling Project
FAQs about Kaggle What is Kaggle? Kaggle, a subsidiary of Google LLC, is an online community of data scientists and machine learning practitioners. Kaggle offers a no-setup, customizable, Jupyter Notebooks environment. Access free GPUs and a huge repository of community-published data & code. Kaggle is a platform where data scientists can compete in machine learning challenges. These challenges can be anything from predicting housing prices to detecting cancer cells. Kaggle has a massive community of data scientists who are always willing to help others with their data science problems. In addition to the competitions, Kaggle also has many tutorials and resources that can help you get started in machine learning. If you are an aspiring data scientist, Kaggle is the best way to get started. Many companies will give offers to those who rank highly in their competitions. In fact, Kaggle may become your full-time job if you can hit one of their high rankings. 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 data science? We have more data than ever before. But data alone cannot tell us much about the world around us. We need to interpret the information and discover hidden patterns. This is where data science comes in. Data science uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction. Data science seeks to find patterns in data and use those patterns to predict future data. It draws on machine learning to process large amounts of data, discover patterns, and predict trends. Data science includes preparing, analyzing, and processing data. It draws from many scientific fields, and as a science, it progresses by creating new algorithms to analyze data and validate current methods. What is Kaggle used for? Kaggle is a website for sharing ideas, getting inspired, competing against other data scientists, learning new information and coding tricks, as well as seeing various examples of real-world data science applications. Is Kaggle free to use? Does Kaggle cost anything? The Kaggle Services may be available at no cost or we may charge a monetary fee for using the Services. What are typical use cases for Kaggle? Kaggle is best for businesses that have data that they feel needs to be analyzed. The most significant benefit of Kaggle is that these companies can easily find someone who knows how to work with their data, which makes solving the problem much easier than if they were trying to figure out what was wrong with their system themselves. What are some popular competitions on Kaggle? There are many different types of competitions available on Kaggle. You can enter a contest in everything from predicting cancer cells in microscope images to analyzing satellite images for changes overtime on any given day. Examples include:
Predicting car prices based on features such as horsepower and distance traveled
Predicting voting patterns by state
Analyzing satellite images to see which countries have the most deforestation
Moving through the course without distractions
You'll also get: Lifetime Access to The Course Fast & Friendly Support in the Q&A section Udemy Certificate of Completion Ready for Download We offer full support, answering any questions. If you are ready to learn Now Dive into; " Kaggle Masterclass with Hearth Attack Prediction Project Kaggle is Machine Learning & Data Science community. Boost your CV with Hearth Attack Prediction Project in Kaggle " course. See you in the course! Who this course is for:
Anyone who wants to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
For those who want to compete in data science and machine learn by learning about Kaggle
Anyone who wants to learn Kaggle
Those who want to improve their CV in Data Science, Machine Learning, Python with Kaggle
Anyone who is interested in Artificial Intelligence, Machine Learning, Deep Learning, in short Data Science
Anyone who have a career goal in Data Science
Anyone who is interested in Artificial Intelligence, Machine Learning, Deep Learning, in short Data Science