When it comes to the outsourcing of programmers, I think I have a better say, even though I have now switched from JAVA development in an outsourcing company to do artificial intelligence algorithms.
I graduated in 2018. The first job I found after graduation was an outsourcing company. My main job was to undertake the projects of Party A, write the code according to the needs of customers, and work day and night to get a little bit. income.
After three years of CRUD, I haven't grown at all, but I have lost a lot of hair. As for why outsourcing companies are not conducive to growth, because generally speaking, outsourcing companies are not cautious enough in the research and development of Party A’s products, as long as they can meet the needs of customers, they lack the attitude towards product design and truly making good products. Of course, this is determined by the nature of the outsourcing company.
No way, I didn’t want to be content with the status quo at the time, so after a long talk with my friends, I decided to switch to the direction of AI algorithms.
The direction from java programmers to AI is absolutely correct, and it is also the only way for some people, because java developers will eventually be diverted to many fields, and some of them will go to higher-level artificial intelligence Go in the direction to break through the existing bottleneck.
If you want to switch to the direction of AI algorithms, you must plan and plan your learning route in advance. I will talk about how to get started with artificial intelligence later.
First of all, start with a machine learning framework, Spark-ml sklearn tensor flow, proficient in its engineering implementation, don't worry about so many internal details, just like you do java calling API, if you are proficient in calling and parameter passing, you can be very good It is not necessary to understand the algorithm itself, which is the case for most AI companies now, and the primary goal is to be able to produce results;
Then, it is to accumulate practical experience desperately. After entering or changing careers, dig deeper and become proficient. It is easier to have the framework + practical experience as the basis, and the salary at this time will definitely be much higher than before. doubled.
When it comes to actual project experience here, this is more important than the framework and academic qualifications. This is an important criterion for whether you can enter a famous company in the future and whether your salary can widen the gap with your peers. There is no shortcut here, you must Although there is no shortcut to the accumulation of each project, there are also choices, such as the company you participated in the training or internship? The institution that participated in the training and learning? The company that changed jobs? Can real algorithms be learned? Can you touch a real robot? These are very critical.
Share some of the artificial intelligence learning materials I have compiled for you for free. It has been compiled for a long time and is very comprehensive. Including some artificial intelligence basic introductory videos + AI common framework practical videos, image recognition, OpenCV, NLP, YOLO, machine learning, pytorch, computer vision, deep learning and neural network and other videos, courseware source code, well-known domestic and foreign elite resources, AI popular Papers, etc.
The following are some screenshots, scan the code at the end of the article and add me to get it for free (I can also answer one or two questions about AI technology)
Table of contents
1. AI Free Video Courses and Projects
2. Artificial intelligence must-read books
3. Collection of Papers on Artificial Intelligence
4. Machine Learning + Computer Vision Basic Algorithm Tutorial
Five, deep learning machine learning cheat sheet (a total of 26)
To learn artificial intelligence well, you need to read more books, do more hands-on work, and practice more. If you want to improve your level, you must learn to calm down and learn systematically slowly, so that you can gain something in the end.