Artificial intelligence (AI) refers to intelligence demonstrated by machines as opposed to natural intelligence demonstrated by animals such as humans. According to leading AI textbooks, the area is defined as the study of "intelligent agents": any system that senses its surroundings and performs actions that maximize its chances of attaining its goals. Some popular reports use the word "artificial intelligence" to denote robots that simulate "cognitive" functions that humans connect with the human mind, such as "learning" and "problem solving," however prominent AI researchers reject this definition.
| S.No | Topics | Link |
|---|---|---|
| 1 | Choose a Programming Language | |
| - | Computer Vision & NLP | Link |
| 2 | Learn About Kaggle | Link |
| 3 | Data Science | Link |
| 4 | Machine Learning | Link |
| 5 | Deep Learning | Link |
| 6 | Model Deployment | Link |
Note:
- Computer Vision & NLP are important if you are working on a specific dataset/problem in that regard they can be used with a variety of both Machine Learning Models and Deep Learning Models, Hence they do not actually fall at a specifc position in the roadmap but it is recommended for every ml developer to have some knowledge about these topics.
- Kickstart Kaggle by Hrithik Purwar
- Decoding Data by Avinash Singh
- Null Code AI by Hrithik Purwar
- Build-A-Bot by Adeel Abdul Sakkeer
- Deep Dive into DL by Aman Ali
- DataViz by Anushka Dixit
- Mathematics for Machine Learning by Mohit Uniyal
- Statistics and Machine Learning by Ashutosh Raj
- How to Design Solutions With AI by Keshav Jangid
- Computer Vision using OpenCV by Jayesh Singh
🎉 Wohoo, that's all for now, Hope you have a great journey ahead!
With ❤️ by ISTE-VIT