Data Science: Instructional Materials


The Value of Exploratory Data Analysis

@machinelearnbot

From the outside, data science is often thought to consist wholly of advanced statistical and machine learning techniques. However, there is another key component to any data science endeavor that is often undervalued or forgotten: exploratory data analysis (EDA). At a high level, EDA is the practic...



Open Machine Learning Course. Topic 2. Visual data analysis with Python

#artificialintelligence

In the field of Machine Learning, data visualization is not just making fancy graphics for reports; it is used extensively in day-to-day work for all phases of a project. To start with, visual exploration of data is the first thing one tends to do when dealing with a new task. We do preliminary checks and analysis using graphics and tables to summarize the data and leave out the less important details. It is much more convenient for us, humans, to grasp the main points this way than by reading many lines of raw data. It is amazing how much insight can be gained from seemingly simple charts created with available visualization tools. Next, when we analyze the performance of a model or report results, we also often use charts and images. Sometimes, for interpreting a complex model, we need to project high-dimensional spaces onto more visually intelligible 2D or 3D figures. All in all, visualization is a relatively fast way to learn something new about your data. Thus, it is vital to learn its most useful techniques and make them part of your everyday ML toolbox. In this article, we are going to get hands-on experience with visual exploration of data using popular libraries such as pandas, matplotlib and seaborn. The following material is better viewed as a Jupyter notebook and can be reproduced locally with Jupyter if you clone the course repository. Before we get to the data, let's initialize our environment: In the first article, we looked at the data on customer churn for a telecom operator. We will load again that dataset into a DataFrame: To get acquainted with our data, let's look at the first 5 entries using head():


Introduction to Machine Learning for Mere Mortals: Solving Common Business Problems with Data Science

#artificialintelligence

Machine learning is one of the hottest topics in tech today. It is a must-have organizational competency in the data-driven era of digital transformation. Despite the unprecedented speed and ease of creating predictive models today, the human mind is still essential for generating good machine learning models. In this fast-paced introductory class, participants will be introduced to fundamental concepts and walk-through the entire machine learning lifecycle with optional hands-on exercises using open source tools. From selecting the right problem to solve to preventing algorithm bias, machine learning is still an art and a science. Participants will learn how machine learning works, how to prevent common mistakes and learn how to build and use machine learning models. Who Should Attend: This course is designed for technical professionals that want to understand how machine learning works, how to best apply it, and how to get started. Topics include:


Learning Data Science on R - Step by Step Guide Learning Path

#artificialintelligence

One of the common problems people face in learning R is lack of a structured path. They don't know, from where to start, how to proceed, which track to choose? Though, there is an overload of good free resources available on the Internet, this could be overwhelming as well as confusing at the same t...


R: Complete Data Analysis Solutions Udemy

@machinelearnbot

If you are looking for that one course that includes everything about data analysis with R, this is it. Let's get on this data analysis journey together. This course is a blend of text, videos, code examples, and assessments, which together makes your learning journey all the more exciting and trul...


WalkMe adds predictive analytics to its platform for optimizing user experience - SiliconANGLE

#artificialintelligence

WalkMe Ltd., maker of a platform for understanding and improving user experience, has added predictive analytics capabilities to its intelligent assistant technology that interprets user behavior to predict next actions and provide context-sensitive responses. The company primarily targets its tech...


The EPFL Extension School

@machinelearnbot

The Applied Data Science: Machine Learning program will give you hands-on experience in one of the hottest areas of data science. You will learn tools for predictive modeling and analytics, harnessing the power of neural networks and deep learning techniques across a variety of types of data sets. Each of the four courses in this program will let you demonstrate your newly-acquired skills through a course project. ECTS credits will be awarded to learners who successfully complete all four courses and course projects as well as a final capstone project. These course details are subject to change; please refer to the program outline at the time of registration.


16 Top-Rated Data Science Courses – Personal Growth – Medium

@machinelearnbot

Note: Some of these courses are free. But if you decide to purchase anything (using the links below) you'll be financially supporting the Personal Growth publication. This course will give you a full overview of the Data Science journey. You'll develop a good understanding of SQL, SSIS, Tableau, and Gretl. This course begins with Tableau basics.


Data Science in Python Pandas, Scikit-learn,Numpy Matplotlib

@machinelearnbot

"This course has taught me many things I wanted to know about pandas. It covers everything since the installation steps, so it is very good for anyone willing to learn about data analysis in python /jupyter environment." "Good explanation, I have laready used two online tutorials on data -science and this one is more step by step, but it is good" "i have studied python from other sources as well but here i found it more basic and easy to grab especially for the beginners. I can say its best course till now . The average data scientist today earns $130,000 a year by glassdoor.