Development of artificial intelligence affects numerous industries. Thus, it becomes important to acquire AI learning skills for staying aware of changes and searching new career paths. This article presents some tips on how one can start learning artificial intelligence.
Understanding Artificial Intelligence Concepts
There exist several key elements related to AI such as machine learning, natural language processing, and computer vision. While studying artificial intelligence concepts, it becomes important to know what narrow and general AI are and how to distinguish supervised and unsupervised learning methods.
A narrow or weak AI model can perform limited number of actions, for example face detection or translation. On the other hand, general AI model, which is also called strong AI, can execute all kinds of human intellectual tasks. Supervised learning method means that one trains a machine with data with labels. An unsupervised method implies using unlabeled data for training AI systems.
Selecting the Correct AI Tools
As there exist several software platforms used in development of AI models, one needs to select the appropriate AI tool depending on particular circumstances. Such popular platforms as TensorFlow, PyTorch, and Keras should be mentioned.
When choosing an AI tool, it is important to take into account many aspects like types of data and the level of complexity. TensorFlow is used to build and train deep learning models. PyTorch is famous for its flexibility. Finally, Keras can be helpful to design neural network architectures.
Using AI Models to Solve Particular Problems
After selecting the correct tool, one should implement his/her own AI solution to solve a problem. These processes involve gathering data, data preprocessing, creating an AI model, training it, testing, and deploying.
While implementing the solution, one needs to perform these operations:
• collect data
• preprocess it
• design an AI model
• train the model with the prepared data
• test the model
• deploy it into production environment.
One should be well-acquainted with the selected tool to successfully complete these operations.
Gaining Proficiency in Programming Languages and Tools
It is obvious that a person who wants to develop AI should have certain programming skills because he/she will have to create, design, and train models. Some popular programming languages are Python, R, and Julia. Python is easy-to-use and flexible; therefore, it is used in the majority of cases in AI. Another language is R, which is popular for statistical computing. As for Julia, it is a relatively new language but its popularity increases fast because of its speed.
Besides knowing languages, one should also be proficient in such fundamental concepts as algorithms and object-oriented programming. Besides, knowledge of specific programming frameworks is necessary.
Applications of AI in Real World Problems
AI has lots of applications in various spheres. One can mention image recognition, NLP, and predictive analytics as examples. An image recognition system is created to identify an object, scene, or a pattern inside a picture. NLP is the technology that allows developing programs that can recognize and generate texts. Predictive analysis means developing models that can forecast something.
However, before applying AI in solving a practical problem, one should know the main AI concepts, programming languages, and tools. To solve image recognition task, one needs to use deep learning models such as CNN, object detection, and other.
Keeping Up with Latest Trends
Since technology advances rather rapidly, one should track AI trends to remain knowledgeable. Some major trends in AI development are explainable AI, transfer learning, and adversarial training. The first trend helps AI make its decisions based on explanations. Transfer learning is used to reuse some preexisting models to improve another one. The third technique deals with training models to resist attacks.
An effective way to stay informed about new AI trends is attending conferences on this topic. One should pay attention to NeurIPS, IJCAI, ICML.
Conclusion
Thus, the present article provided some basic concepts related to AI, and highlighted necessary steps to become an AI specialist.
