Build and train a data model to recognize objects in images!

--- **Overview of Course Review** The online course on implementing image recognition projects has received a global rating of 4.55 from recent reviews. The course is generally considered helpful for students with limited knowledge of the subject, though some reviewers pointed out issues with the course structure and repetitive content. Here's a detailed breakdown of the feedback: **Pros:** - **Comprehensive Content:** The course provides great content that is very well explained, covering the basics of Python and TensorFlow, assuming minimal prior knowledge. This makes it an excellent starting point for beginners. - **Clear Explanations:** The instructor's explanations of key concepts are considered clear and beneficial, aiding in understanding the material effectively. - **Stepping Stone:** The course is viewed as a good stepping stone into more complex subjects within machine learning and image recognition. - **Ease of Implementation:** The course guides learners through implementing real projects, which is highly appreciated by those who have completed the course. - **Quality of Instruction:** The instructor is described as wonderful, explaining concepts in a way that is understandable for beginners. **Cons:** - **Visual Distractions:** Some reviewers find the course to be loaded with unnecessary animations and visual effects, which are distracting, particularly for individuals with ADD or similar attention challenges. - **Redundant Information:** There is a recurring issue where the same information is explained multiple times. For instance, explaining how to install a Python module or run a script more than once is seen as redundant. - **Annoying Intro/Outro:** The presence of an intro and outro before every single video can disrupt the flow of learning and is viewed negatively by some learners. - **Lack of Consistency in Video Content:** It appears that most of the videos are recycled from other courses, which might lead to redundancy if a learner decides to take additional courses. - **Instructor Availability:** The instructor seems unavailable for addressing questions in the Q&A section, which can be a significant drawback for learners seeking guidance. - **Technical Issues:** Some reviewers encountered technical difficulties with running the examples provided in the course, suggesting that there might be issues with TensorFlow installation. - **Repetitive Content:** The course occasionally reads out code loud, which is unnecessarily repetitive and could be skipped. - **Unclear Instructions:** There are instances where the instructions given for certain tasks or code execution are not clear, leading to confusion among learners. - **Unresponsive Q&A:** The instructor does not answer questions in the Q&A, which is a critical aspect of learning and can be frustrating for learners seeking assistance. **Additional Notes:** - Learners are advised to have Tensorflow version 1.x - 2.0, and specifically use Cuda 10 if using tensorflow-gpu, as well as download Nvidia cuDNN separately. - Some learners experienced issues with running the examples provided in the course, which might be due to having a different TensorFlow installation. It is recommended to ensure that the environment matches the one assumed by the course for optimal learning experience. **Conclusion:** Overall, the course is a valuable resource for beginners looking to learn image recognition with Python and TensorFlow. Despite some issues with the course structure and redundancy, the comprehensive content and clear explanations make it stand out as a beneficial learning tool. However, potential learners should be aware of the lack of responsiveness from the instructor and consider the necessity of their TensorFlow environment setup before enrolling.