foreword
Algorithm recommendation, intelligent security, machine learning, predictive analysis... These concepts that once appeared in science fiction are relying on big data to penetrate our life, consumption and work. Especially for technology developers, your work is becoming more and more closely related to big data, and it will become even closer in the future. Whether you are engaged in big data-related work or not, you must master the principles and architecture of big data.
On the other hand, there is a huge talent gap in the big data industry, and the salary has risen by 70% in the past five years. For engineers who want to enter the big data industry and win better development with dividends, now is the right time to enter the industry.
5 modules
This tutorial connects data production, data collection, data transmission, data storage, data mining, data analysis, and data application, which is a chain of data circulation, to explain the big data system for you. It is divided into 5 modules, with a total of 22 articles:
Introduction to Module Big Data
First of all, the column will use an interesting and life-like case like "weather forecast" to help you quickly understand big data, and then introduce you to the past, present, and future development trends of big data, helping you understand the complete system and appearance of big data , so that when your future work involves the application of big data, you can quickly locate the needs and choose the skill points you need to further study.
Module 2 Big Data Architecture
The column will use the big data design cases of well-known Internet companies such as Ali, NetEase, Didi, etc., to take you to understand the application of big data in the company's actual scenarios: understand their big data architecture, and how the big data system has evolved to today appearance, and then starting from the most common part, to explain the important components of Hadoop's entire ecology.
Module three major data development
This part introduces the various big data tools most commonly used in Internet companies, which may use simple codes to get a preliminary understanding, so that you can understand what it is and what it can do, so that you can meet such needs in future work , you can get started quickly. At the same time, it will sort out for you how each link of the big data system operates independently in the actual development work, and how it is connected with the upstream and downstream.
Module 4 Data Mining and Analysis
This module will take you to understand the whole process of standardized data mining and the four classic algorithms of data mining. You will learn how data mining algorithms work under the company's big data system, how to bring business value to the company, and which mainstream algorithms need to be focused on.
Module five major data applications and security
Analyze the application cases of recommendation system, data operation, and data center for you. You will understand that big data systems are not castles in the air, they have very rich applications. The knowledge in this module can help you empower your business with big data.
Lecturer profile
Senior Algorithm Expert of Arakawa First-line Manufacturer
He is currently a senior algorithm expert and a senior data person in BAT's first-line Internet company. He has participated in hundreds of millions of recommendation system related work, involving the development and management of system architecture, content understanding, user portraits and other aspects. He has led large-scale projects such as data platform construction, recommendation system data flow framework design, digital content operation platform, user portrait platform, etc., and is familiar with the upstream and downstream work of the big data system with personalized recommendation as the application.
Catalog/A total of 25 sections
opening words
Opening Remarks | How to clarify the path in the huge big data system?
Module 1: Introduction to Big Data
01 | What is big data from the weather forecast
02 | From budding to outbreak, what development has big data experienced?
03 | In order to catch up with the current trend, what mental preparation do we have to do?
Module 2: Big Data Architecture
04 | What kind of big data architecture are big companies like Ali Meituan using?
05 | An essential tool for big data development - Hadoop
Module 3: Big Data Development
06 | Accurate traceability: where does the data in big data come from?
07 | HDFS specially designed to solve big data storage problems
08 | Can you tell the difference between HBase and Hive?
09 | Let you fully understand why big companies are doing cloud services
10 | How to choose between the message system Kafka and Flume
11 | What are the basic ideas of MapReduce processing big data
12 | Love and hatred between Spark and Flink (Part 1)
13 | Love and hatred between Spark and Flink (Part 2)
Module 4: Big Data Mining and Analysis
14 | Take you to talk about the whole process of standardized data mining
15 | Let you understand the four classic algorithms of data mining at a glance
16 | Computer vision VS natural language processing, which one do you choose?
17 | How to deeply analyze the value of e-commerce data?
18 | Data Visualization: How to "see" data intuitively?
Module Five: Big Data Application and Security
19 | How to quickly build a recommendation system?
20 | How to do data operation from scratch?
21 | How to protect privacy in big data environment?
22 | Data Center: Enabling Business with Big Data
eggs
Easter eggs | In the era of big data, where will the future go?
conclusion
Conclusion | Those who get big data win the world
Network disk content
Summarize
Two types of people are common when studying:
One is collectors,
I was reluctant to watch the video, for fear that it would be ruined.
The second is the anticlimactic man,
Sprint when you run together, give up when you get frustrated...
You have to work hard but not too hard,
Pushing too hard can unconsciously raise expectations,
Once expectations are not met during this process,
You will be very disappointed and frustrated.
Everything that is too hard on the surface is hard work,
In fact, it is easy to trigger because of a straw,
And all overwhelmed...
Like a clockwork that is stretched too tightly, it is more likely to break.
It is anticlimactic because the rhythm is not well controlled.
We must persevere long and effortlessly,
Instead of passion and tortured effort.
