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Ensemble Machine Learning in Python: Random Forest, AdaBoost

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Free Coupon Discount - Ensemble Machine Learning in Python: Random Forest, AdaBoost, Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical Machine Learning for Data Science in Python Created by Lazy Programmer Inc. Students also bought Unsupervised Deep Learning in Python Machine Learning and AI: Support Vector Machines in Python Data Science: Natural Language Processing (NLP) in Python Deep Learning: Advanced Computer Vision (GANs, SSD, More!) Deep Learning Prerequisites: Linear Regression in Python Preview this Udemy Course GET COUPON CODE Description In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning. Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning. Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.


12 Best Deep Learning Courses on Coursera

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This is another specialization program offered by Coursera. This specialization program is for both computer science professionals and healthcare professionals. In this specialization program, you will learn how to identify the healthcare professional's problems that can be solved by machine learning. You will also learn the fundamentals of the U.S. healthcare system, the framework for successful and ethical medical data mining, the fundamentals of machine learning as it applies to medicine and healthcare, and much more. This specialization program has 5 courses. Let's see the details of the courses-


Deep Learning Prerequisites: Logistic Regression in Python

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This course is a lead-in to deep learning and neural networks - it covers a popular and fundamental technique used in machine learning, data science and statistics: logistic regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own logistic regression module in Python. This course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for free.


Deep Learning Prerequisites: Linear Regression in Python

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Deep Learning Prerequisites: Linear Regression in Python, Data science: Learn linear regression from scratch and build your own working program in Python for data analysis. Created by Lazy Programmer Inc. Preview this Course  - GET COUPON CODE 100% Off Udemy Coupon . Free Udemy Courses . Online Classes


7 Best Free Computer Vision Courses

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This is a Free to Audit course on Coursera. That means you can access the course material free of cost but for the certificate, you have to pay. In this course, you will understand the basics of computer vision and learn color, light, and image formation; early, mid-level, and high-level vision; and mathematics essential for computer vision. Throughout this course, you will apply mathematical techniques to complete computer vision tasks. You will get a free license to install MATLAB for the duration of the course is available from MathWorks.


Learning Resources for Machine Learning - Programmathically

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Familiarity with basic statistics and mathematical notation is helpful. An Introduction to Statistical Learning is one of the best introductory textbooks on classical machine learning techniques such as linear regression. It was the first machine learning book I've bought and has given me a great foundation. The explanations are held on a high level, so you don't need advanced math skills. Every chapter comes with code examples and labs in R. It is a great book to work through cover-to-cover. Get "An Introduction to Statistical Learning" on Amazon


Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence

arXiv.org Artificial Intelligence

Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.


Intro to Deep Learning project in TensorFlow 2.x and Python

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The Black Friday Udemy sale begins. Shop to save on thousands of online courses. Welcome to the Course Introduction to Deep Learning with TensorFlow 2.0: In this course, you will learn advanced linear regression technique process and with this, you can be able to build any regression problem. Using this you can solve real-world problems like customer lifetime value, predictive analytics, etc. All the above-mentioned techniques are explained in TensorFlow.


Machine Learning and Deep Learning A-Z: Hands-On Python

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Learn Machine Learning with Hands-On Examples What is Machine Learning? Machine Learning Terminology Evaluation Metrics for Python machine learning, Python Deep learning What are Classification vs Regression? Evaluating Performance-Classification Error Metrics Evaluating Performance-Regression Error Metrics Cross Validation and Bias Variance Trade-Off Use matplotlib and seaborn for data visualizations Machine Learning with SciKit Learn Linear Regression Algorithm Logistic Regresion Algorithm K Nearest Neighbors Algorithm Decision Trees And Random Forest Algorithm Support Vector Machine Algorithm Unsupervised Learning K Means Clustering Algorithm Hierarchical Clustering Algorithm Principal Component Analysis (PCA) Recommender System Algorithm Python, python machine learning and deep learning Machine Learning, machine learning A-Z Deep Learning, Deep learning a-z Machine learning is constantly being applied to new industries and new problems. Whether you're a marketer, video game designer, or programmer 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. What is the best language for machine learning? 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. Python instructors on Udemy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction What are the limitations of Python? Python is a widely used, general-purpose programming language, but it has some limitations.


The Data Analyst Course: Complete Data Analyst Bootcamp 2021

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Created by Andrei Neagoie, Daniel BourkePreview this Course - GET COUPON CODE This is a brand new Machine Learning and Data Science course just launched and updated this month with the latest trends and skills for 2021! Become a complete Data Scientist and Machine Learning engineer! Join a live online community of 400,000 engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. Graduates of Andrei's courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, other top tech companies. You will go from zero to mastery! Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries).