Learn and Test your Machine Learning Skills with AV’s New Practice Problems and Free Courses!
“Knowledge is of no value unless you put it into practice.” – Anton Chekhov
Gaining knowledge of new concepts is a critical aspect of data science and machine learning. But the real gold lies in putting these concepts into practice. The more you practice, the better your concepts become!
I am excited to announce that Analytics Vidhya has launched two brand new practice problems for both machine learning and deep learning enthusiasts and experts. We have also added three new courses to our burgeoning training portal. These courses cover a variety of challenges machine learning folks will find useful.
We believe in providing only top class content for our community and our trainings, hackathons, articles and practice problems reflect that commitment. Let’s look at these practice problems and training courses in a bit more detail.
Analytics Vidhya’s practice problems bring out the data scientist within you. Our collection of practice problems span varying domains – performing sentiment analysis, building recommendation systems, prediction loan default, identifying digits from images, estimating the age of Indian actors, among a whole host of other challenges.
We are excited to launch two new practice problems:
This is an intriguing computer vision problem which has been recently gained a lot of traction in the deep learning community.
The dataset we are providing for this is called ‘Fashion MNIST’. It’s inspired from MNIST, a very popular dataset in the machine learning community (you can check out the MNIST practice problem in our ‘Identify the digits’ challenge). In ‘Identify the apparels’, instead of digits the images show a type of apparel, e.g. tee-shirt, trousers, bag, etc. The dataset used in this problem was created by Zalando Research.
This practice problem is meant for beginners in deep learning. Intermediate or experts in this field can also work on this to refresh their concepts.
This is quite a unique practice problem. You are challenged with predicting the ratings for jokes given by the users provided the ratings provided by the same users for another set of jokes. This dataset has been taken from the famous jester online Joke Recommender system dataset.
This practice problem is meant for everyone in the machine learning field – from beginners to experts. I recommend getting familiar with recommendation systems to get the most from this challenge.
Courses and Trainings
Analytics Vidhya’s aim has always been to build and help data scientists all over the globe by providing top notch training resources. So, we have expanded our training catalogue exponentially this year. We launched the ‘Introduction to Data Science‘ course which has quickly become our most popular training. We also have trainings on Excel and problem solving using data, and of course a comprehensive learning path to become a data scientist.
We have recently added three more exciting trainings to this list!
Time Series forecasts come in handy for creating simple forecasts like number of airline passengers, website traffic, etc. This course is a comprehensive guide to getting you started in this vast and intriguing domain. Time Series forecasting is a skill every data scientist should have in their skillset so ensure you take this course!
This course is meant for newcomers in data science and machine learning. Predicting the sales of a business is one of the most common challenges in this field and this course will give you a very good idea of how to approach this challenge. This course will equip you with the skills and techniques required for solving a regression problem in R.
This course is designed for people who want to learn how to solve binary classification problems. In this course, you will solve a real life case study of Dream Housing Finance. The company wants to automate the loan eligibility process (real-time) based on the customer details provided through an online application form.
By the end of the course, you will have a solid understanding of classification problems and various approaches to solve them.