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Thanks for sharing this content with us. Really amazing blog Please keep posting.!!! I recomended also visit: college. Basic Statistics week eight its exam time this is the final week in which you have to pass the final exam of Basic Statistics course.

What does the test statistic tell you? It indicates how many standard errors a point estimate lies from the expected null hypothesis population value.

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It's another word for the p-value. It indicates whether you should use z- or t-distribution to calculate probability. It indicates how far from the actual population value your sample mean lies.

Coursera: Machine Learning (Week 2) Quiz - Octave / Matlab Tutorial | Andrew NG

You are going to select an individual from the group of students. The probability of event A is equivalent to the probability that you select someone who studies social science sociology, political science and anthropology or physics.

In your sample you find a value that is lower than 6. Is it 'easier' to reject the null hypothesis with a one-tailed or two-tailed test? A one-tailed test. A two-tailed test. This depends on the level of significance. This depends on the P value. Someone makes the following assertion: if the sample becomes larger, then the standard deviation becomes smaller.

Which of the following statements is correct? This assertion does not apply to any distribution. This assertion always applies to all distributions. This assertion always applies to the sample distribution and the sampling distribution. This assertion always applies to the sampling distribution.

The largest number of Oscars received by a film in year X was 4. This was different in previous years. Below is a probability distribution for the number of Oscars per Oscar winning film. What is the standard deviation of this distribution?

Number of Oscars. What type of table is shown below? Gini Index. The Netherlands.Studying can feel like an enormous challenge, especially when tests and exams are looming. We will help you to find studying easier than perhaps it has been to this point.

Studying becomes much faster as soon as you can check your answers so you won't be stuck.

how to find coursera quiz answers

We're supporting the most popular courses in U. Meet hundreds of students discussing questions and giving them the answers. We're working hard to support as many courses as possible, so you can always find the needed one.

At no charge. Coursera is a powerful tool for free online education, and includes courses from many top universities, museums and trusts. Bringing together courses from many different schools, the site has impressive, quality information for everyone. SoloLearn is an online and mobile learning platform that offers free coding classes in 13 different programming disciplines.

Upwork is a global freelancing platform where businesses and independent professionals connect and collaborate remotely. Curating many courses from around the web, Khan Academy offers impressive depth on many different subjects. Cisco Networking Academy works toward a single goal: fostering the technical that people need to change the world for the better.

What interferer can be seen using the Cisco CleanAir technology? Microwave ovens What authentication method would you choose if your guest users need to be greeted with…. Where would Wireless Access Points likely be found? Choose 3 Beacon frame: Sends periodically from….

What are three basic parameters to configure on a wireless access point? Choose three. The simplest and fastest way to find out correct answers for tests, modules, quizzes, assignments on the most popular educational platforms and services like Coursera, edX, Cisco Networking Academy, Sololearn, Upwork etc. Quizzes Answers Make Studying Easy. Search for:. Make Studying Easy. Quizzes answers. Faster studying Studying becomes much faster as soon as you can check your answers so you won't be stuck.

Actual courses We're supporting the most popular courses in U.

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Quizzes Answers is totally free. Coursera EdX Cisco Upwork.There will be an object called 'iris' in your workspace. In this dataset, what is the mean of 'Sepal. Length' for the species virginica?

Please only enter the numeric result and nothing else. Continuing with the 'iris' dataset from the previous Question, what R code returns a vector of the means of the variables 'Sepal. Length', 'Sepal. Width', 'Petal. Length', and 'Petal. There will be an object names 'mtcars' in your workspace. You can find some information about the dataset by running. How can one calculate the average miles per gallon mpg by number of cylinders in the car cyl? Continuing with the 'mtcars' dataset from the previous Question, what is the absolute difference between the average horsepower of 4-cylinder cars and the average horsepower of 8-cylinder cars?

Can you please explain the following line of code which is used in the question 4.

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Embed Embed this gist in your website. Share Copy sharable link for this gist. Learn more about clone URLs. Download ZIP. The data can be loaded with the code: library datasets data iris. Length ]. This comment has been minimized. Sign in to view. Copy link Quote reply. Answer 1 and 4 are not correct as shown in my case. Will you please review it.

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Hi, Can you please explain the following line of code which is used in the question 4. Thanks in advance. Sign up for free to join this conversation on GitHub.

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Already have an account? Sign in to comment. You signed in with another tab or window.About This Specialization This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods.

how to find coursera quiz answers

Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice.

Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings. Projects Overview You will master your skills by solving a wide variety of real-world problems like image captioning and automatic game playing throughout the course projects. You will gain the hands-on experience of applying advanced machine learning techniques that provide the foundation to the current state-of-the art in AI.

Course can be found here Lecture slides can be found here.

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About this course: The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding. The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks.

Learners will study all popular building blocks of neural networks including fully connected layers, convolutional and recurrent layers. Learners will use these building blocks to define complex modern architectures in TensorFlow and Keras frameworks.

In the course project learner will implement deep neural network for the task of image captioning which solves the problem of giving a text description for an input image. The prerequisites for this course are: 1 Basic knowledge of Python.

Please note that this is an advanced course and we assume basic knowledge of machine learning.

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You should understand: 1 Linear regression: mean squared error, analytical solution. Derivatives of MSE and cross-entropy loss functions. Who is this class for: Developers, analysts and researchers who are faced with tasks involving complex structure understanding such as image, sound and text analysis. Apply a softmax transform to it and enter the first component accurate to 2 decimal places.

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Suppose you are solving a 5-class classification problem with 10 features. How many parameters a linear model would have? There is an analytical solution for linear regression parameters and MSE loss, but we usually prefer gradient descent optimization over it. What are the reasons? Gradient descent is more scalable and can be applied for problems with high number of features. Gradient descent is a method developed especially for MSE loss.

Gradient descent can find parameter values that give lower MSE value than parameters from analytical solution. Overfitting is a situation where a model gives lower quality for new data compared to quality on a training sample.

Overfitting happens when model is too simple for the problem. Overfitting is a situation where a model gives comparable quality on new data and on a training sample. Large model weights can indicate that model is overfitted 1 point 2.

What disadvantages do model validation on holdout sample have? It is sensitive to the particular split of the sample into training and test parts. It can give biased quality estimates for small samples ,1,13, 3,12,2 Select correct statements about regularization:.

Weight penalty reduces the number of model parameters and leads to faster model training. Reducing the training sample size makes data simpler and then leads to better quality. Regularization restricts model complexity namely the scale of the coefficients to reduce overfitting.This course gives you easy access to the invaluable learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines.

Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. This course can be taken independent of, concurrent with, or prior to, its companion course, Mindshift. Learning How to Learn is more learning focused, and Mindshift is more career focused.

Founded inMcMaster University is committed to creativity, innovation, and excellence by inspiring critical thinking, personal growth, and a passion for learning.

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U. News and World Report.

Learning How to Learn: Powerful mental tools to help you master tough subjects

Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory. Although living brains are very complex, this module uses metaphor and analogy to help simplify matters.

You will discover several fundamentally different modes of thinking, and how you can use these modes to improve your learning. You will also be introduced to a tool for tackling procrastination, be given some practical information about memory, and discover surprisingly useful insights about learning and sleep. Chunks are compact packages of information that your mind can easily access.

In this module, we talk about two intimately connected ideas—procrastination and memory. Building solid chunks in long term memory--chunks that are easily accessible by your short term memory—takes time. This is why learning to handle procrastination is so important.

Ultimately, you will learn more about the joys of living a life filled with learning! I hope to have gained some useful tools to beat my procrastination; at the very least this course has given me the ability to identify when I slip into procrastinating and methods to break that cycle.

It was a wonderful journey of learning how to learn. Simple and effective. Wish i had come across something like this a little early in life. But better late than never. Keep up the good work.

This course showed me powerful tools to enhance my performance and to achieve a better life quality.To help you better understand Coursera and be successful in it, I am happy to share my own experience on taking a Coursera online course. Here are three reasons why I took it:. The course name is Buddhism and Modern Psychology which is a six-week long learning period, and it turned out to be an extraordinary learning experience. By sharing my learning experience and reflection, it may help future Coursera learners be more successful.

A long time ago I registered another two Coursera courses, but I ended up only finishing the first-week course due to my own laziness. Unlike traditional courses, you will not receive any punishment by not showing up or not finishing assignments in Coursera.

So this time I have to pick a course that I am either strongly interested or beneficial to my career so that I would be motivated to finish the course. Once you choose the course you deeply love, you just need to make a commitment to it. Just like other traditional courses, I went through the course syllabus and borrowed textbooks from library one week before the course officially begin.

I also played around on the Coursera platform a little bit to get familiar with the Learning Management System. I strongly recommend you do the same to save yourself time later.

how to find coursera quiz answers

In Coursera you will only get scores and feedback from peers instead of professors. But later, I found that this new grading system provides me much more beyond the traditional classroom. I have received some considerate and long comments from peers, which encourage me to rethink some critical concepts.

Lots of people are questioning whether online learning is capable of high-quality interaction. In fact, Coursera does have high-quality interaction!

The discussion forum is the main tool for learners to interact with each other and exchange ideas and opinions. These mentors just like TAs in traditional classes—they previously achieved good scores in the same course and now love to help new learners.

Another interaction between learners and the instructor in some courses is the Office Hours where the instructor creates a new video every week to answer the most emergent and difficult questions from that week. With the help of social media, for example, Twitter, Facebook, and discussion forums, the instructor is able to collect many interesting questions and respond via a short video or announcement. Even though it may take some time to adapt these new tools and methods, it can be very effective if we adapt them enthusiastically.

The only thing you need to do is to be open and present! The workload for my course was about 6 hours a week. Basically, I watch some lecture videos and finish some readings every week. There are only two essay assignments throughout the course.

The challenge for me is that I have to work in the day, so I have to study for this course at night or on the weekends. Once, I missed one week of content due while traveling and I had to catch-up by finishing two weeks of the course within one weekend, which was a painful experience.

how to find coursera quiz answers

So my suggestion is to finish the weekly content as soon as possible and do not wait until the last minute. Looking back, the overall Coursera experience was fantastic! Getting a I also read lots of books and gained new knowledge and understanding in psychology and religion.

My tips might not apply to every Coursera course because every course is designed differently, but it will remind you to keep open-minded to new ways of learning and continuously learn, grow and share in the world classroom. Thank you for the comment! Your comment must be approved first.The aim for the course is to teach people how to learn more effectively, in any type of study or topic.

Professor Oakley provides far-reaching and practical insight not only from neuroscience and cognitive psychology, but from decades of practical experience teaching tough university-level courses. In a recent interview with Popular Science radioProfessor Oakley explained how during middle and high school, she failed math, and therefore invested her time in learning languages.

To eventually obtain her Ph. Her book and the course include advice and techniques on how to study well, and—as importantly—how to avoid bad, detrimental study habits. We hope apply them to your studies on Coursera! Penguin, July We hope these rules will help you study better on Coursera. Share on Facebook Share. Share on Twitter Tweet. Share on LinkedIn Share. Send email Mail. Passive rereading. Sitting passively and running your eyes back over a page. Unless you can prove that the material is moving into your brain by recalling the main ideas without looking at the page, rereading is a waste of time.

Letting highlights overwhelm you. A little highlighting here and there is okay—sometimes it can be helpful in flagging important points. But if you are using highlighting as a memory tool, make sure that what you mark is also going into your brain.

This is one of the worst errors students make while studying. You need to be able to solve a problem step-by-step, without looking at the solution. Waiting until the last minute to study.

Would you cram at the last minute if you were practicing for a track meet? Your brain is like a muscle—it can handle only a limited amount of exercise on one subject at a time.