March 9, 2017 at 18:21Learning can be fun, learning can be effective
Hello, Habr! Raise your hand those who are already a little tired of this noise associated with Big Data?
It also seems to me that this topic is already a little fed up with everyone. Every week, a large number of articles fall out on this topic on Habré, on Medium, on Facebook, on LinkedIn, on a bunch of other thematic sites that send letters to the mailbox. Everyone wants to share their experience, their thoughts, their plans, making this stream of information intolerable.
But if you agree with this, then why did you click on this post? What do you expect from him?
Such is the reality that you are unlikely to get something truly valuable from an average article. Remember when this happened the last time, when you went to some post or some article, read it and went immediately to change something in your life? This happens when you are looking for something purposefully. You have a motivation for this. Something does not work for you, it doesn’t work, there is some problem, or there are some formulated desires.
And when you absorb articles, news on a certain topic just like that? What does it mean?
Maybe here lurking for you are not formulated desires?
Maybe you feel that there is something apart from the noise?
Maybe you feel that this is the future, and you want to be part of it?
Maybe you want to live at the forefront of technology, rather than wait for a wave of change to sweep you away?
If so, then formulate it for yourself, finally.
If so, then stop reading articles about it “for general development.” They do not bring you closer to the fulfillment of desire. They do not help you get closer to your goal. They just give an imaginary sense of movement.
But if you really want this, you need to approach this matter in a completely different way.
You probably have a picture in your head:
“Yeah, I need to spend a couple of years getting fundamental knowledge: mat. analysis, linear algebra. statistics, probability theory, optimization methods, theory of algorithms, and more. etc. After that I will be ready to spend another year mastering more applied things: descriptive analysis, predictive analysis, causal analysis, machine learning, date mining, and many others. etc. And only after that I will be ready to solve real problems. ”
Wow, wow, easier.
This method has the right to life, but it is very difficult and boring. He has a very long feedback loop. Few can overpower the way in this form. Only those who have strong self-discipline, those who have the habit of completing what they have begun, no matter how much they like this process.
In his educational programwe approach differently. We teach how to solve real problems, we teach applied things, we give theory and fundamental knowledge exactly as much as is necessary to solve real problems. And all this in 3 months. After that, you can study fundamental things as much as you like. The Internet is full of resources for this. But they will fall on you in a completely different way. You will understand why this is for you. Connections will be made in your brain with what you already know how to practice. We consider this approach more effective (and not only we, andragogy was invented in the 19-20 century). Plus you get feedback very quickly.
According to the results of the first first weekyou can deploy your cluster of 4 machines and run map-reduce job on it. You can come to work after that and tell your colleagues: “I can do this thing.” They will envy.
In the second week, you learn to filter users in the logs of visits to Internet pages and put it in a distributed database, plus you can extract the top 350 url from the same logs. All this with map-reduce on the cluster.
According to the results of the third week, you are able to classify users according to the log of visits using heuristic rules, as well as find relevant domains for motorists. This means that on these sites you can advertise cars! Used technology: map-reduce and hive.
In the fourth weekyou learn to predict the outflow of bank customers. For this, machine learning tools are used.
Fifth week. You can classify reviews of films into positive and negative, as well as determine the similarity of vacancies. To do this, you use machine learning and word processing technologies.
According to the results of the sixth week, you are able to determine the gender and age of a person based on his history of visiting sites, using machine learning and a map-reduce data processing paradigm.
This concludes our first module. You already know how to solve a dozen real tasks.
The second module is dedicated to recommender systems.
Seventh week.You can select non-personalized recommendations for films: various tops and ratings. You already do this on another big data tool - Apache Spark.
Based on the results of the eighth week, you can build recommendations for online courses based on the similarity of their descriptions. Tool: Spark.
In the ninth week, you learn to make collaborative recommendations. This means that you can offer users those products that people like them buy. Or another option, when you offer those products that for some reason are bought together by the same users. Use Spark to solve these problems.
Tenth week.You are trying to build the best movie recommendation system by competing with each other in its quality. Use Spark for this.
According to the results of the eleventh week, you can do real-time processing of tweets.
Twelfth week. Last lab. You are building a recommendation system for an online store. You have a list of products that you need to recommend something worthwhile. You can use absolutely any approaches that have already been studied by this time.
High school graduation.You walk with bulging eyes, not understanding how you even managed to learn how to solve so many real problems in such a short period of time. After that, a clear statement appears in your head: “For me, nothing is impossible. I am capable of mastering any new business. ”And we deliberately designed the program so that you exit with such a feeling.
In general, learning can be fun, learning can be effective!
Among our graduates (there are already about 200 of them) there are even those people who before our program did not program at all, but following the results of the program were able to get into the top 5 best students.
So nothing is impossible if you really want something! Remember why you decided to read this article.
It also seems to me that this topic is already a little fed up with everyone. Every week, a large number of articles fall out on this topic on Habré, on Medium, on Facebook, on LinkedIn, on a bunch of other thematic sites that send letters to the mailbox. Everyone wants to share their experience, their thoughts, their plans, making this stream of information intolerable.
But if you agree with this, then why did you click on this post? What do you expect from him?
Such is the reality that you are unlikely to get something truly valuable from an average article. Remember when this happened the last time, when you went to some post or some article, read it and went immediately to change something in your life? This happens when you are looking for something purposefully. You have a motivation for this. Something does not work for you, it doesn’t work, there is some problem, or there are some formulated desires.
And when you absorb articles, news on a certain topic just like that? What does it mean?
Maybe here lurking for you are not formulated desires?
Maybe you feel that there is something apart from the noise?
Maybe you feel that this is the future, and you want to be part of it?
Maybe you want to live at the forefront of technology, rather than wait for a wave of change to sweep you away?
If so, then formulate it for yourself, finally.
If so, then stop reading articles about it “for general development.” They do not bring you closer to the fulfillment of desire. They do not help you get closer to your goal. They just give an imaginary sense of movement.
But if you really want this, you need to approach this matter in a completely different way.
You probably have a picture in your head:
“Yeah, I need to spend a couple of years getting fundamental knowledge: mat. analysis, linear algebra. statistics, probability theory, optimization methods, theory of algorithms, and more. etc. After that I will be ready to spend another year mastering more applied things: descriptive analysis, predictive analysis, causal analysis, machine learning, date mining, and many others. etc. And only after that I will be ready to solve real problems. ”
Wow, wow, easier.
This method has the right to life, but it is very difficult and boring. He has a very long feedback loop. Few can overpower the way in this form. Only those who have strong self-discipline, those who have the habit of completing what they have begun, no matter how much they like this process.
In his educational programwe approach differently. We teach how to solve real problems, we teach applied things, we give theory and fundamental knowledge exactly as much as is necessary to solve real problems. And all this in 3 months. After that, you can study fundamental things as much as you like. The Internet is full of resources for this. But they will fall on you in a completely different way. You will understand why this is for you. Connections will be made in your brain with what you already know how to practice. We consider this approach more effective (and not only we, andragogy was invented in the 19-20 century). Plus you get feedback very quickly.
According to the results of the first first weekyou can deploy your cluster of 4 machines and run map-reduce job on it. You can come to work after that and tell your colleagues: “I can do this thing.” They will envy.
In the second week, you learn to filter users in the logs of visits to Internet pages and put it in a distributed database, plus you can extract the top 350 url from the same logs. All this with map-reduce on the cluster.
According to the results of the third week, you are able to classify users according to the log of visits using heuristic rules, as well as find relevant domains for motorists. This means that on these sites you can advertise cars! Used technology: map-reduce and hive.
In the fourth weekyou learn to predict the outflow of bank customers. For this, machine learning tools are used.
Fifth week. You can classify reviews of films into positive and negative, as well as determine the similarity of vacancies. To do this, you use machine learning and word processing technologies.
According to the results of the sixth week, you are able to determine the gender and age of a person based on his history of visiting sites, using machine learning and a map-reduce data processing paradigm.
This concludes our first module. You already know how to solve a dozen real tasks.
The second module is dedicated to recommender systems.
Seventh week.You can select non-personalized recommendations for films: various tops and ratings. You already do this on another big data tool - Apache Spark.
Based on the results of the eighth week, you can build recommendations for online courses based on the similarity of their descriptions. Tool: Spark.
In the ninth week, you learn to make collaborative recommendations. This means that you can offer users those products that people like them buy. Or another option, when you offer those products that for some reason are bought together by the same users. Use Spark to solve these problems.
Tenth week.You are trying to build the best movie recommendation system by competing with each other in its quality. Use Spark for this.
According to the results of the eleventh week, you can do real-time processing of tweets.
Twelfth week. Last lab. You are building a recommendation system for an online store. You have a list of products that you need to recommend something worthwhile. You can use absolutely any approaches that have already been studied by this time.
High school graduation.You walk with bulging eyes, not understanding how you even managed to learn how to solve so many real problems in such a short period of time. After that, a clear statement appears in your head: “For me, nothing is impossible. I am capable of mastering any new business. ”And we deliberately designed the program so that you exit with such a feeling.
In general, learning can be fun, learning can be effective!
Among our graduates (there are already about 200 of them) there are even those people who before our program did not program at all, but following the results of the program were able to get into the top 5 best students.
So nothing is impossible if you really want something! Remember why you decided to read this article.