Machine Learning Practical Workout | 8 Real-World Projects (Udemy.com)

While the course provides a good foundational understanding, it's unfortunately not up to date with the latest technologies. Several functions and methods used throughout the lessons are deprecated or no longer supported in current versions of the tools and frameworks. I recommend the instructor revise the content to align with the latest versions and practices so learners can apply the skills effectively in real-world projects.

This is more hands-on type of class, it is well paced with practical projects; seeing how things work makes it much easier to under the theory. I'm software engineer with limited Python experience, and no prior exposure to data science. Surprisingly it doesn't give me much trouble to finish all the projects, I'm starting to apply FB prophet to my work. a few issues that I ran into - a few functions have been dropped in Python 3.10 and latest Keras, has to use newer functions - in project 8, "Movies_id_Titles" file is missing .csv extension, need to manually add the file extension

This course a nice series of applied projects. The level is for beginner and intermediate knowledge backgrounds. Some lectures are redundant, but due to the aim of keeping all people on board of a project session. Don't expect deep details, it is the presentation of standard approaches to solve problems, you may encounter in a business analyst position. Overall, was nice to attend.

Personally enjoyed this course so thank you to the instructor for delivering the course material well. Each project picks a near real-life scenario and an easy to follow step-by-step approach for problem solving. Explanation for Math concept behind is useful so keep it up. For future improvement, suggest to include 'unclean' data sets and walk through the process to clean and prepare data for model training. For each project, use more than 1 activation function, 1 loss function, 1 optimizer function; compare and finetune the predicted classifier. Will be beneficial to include some unsupervised ML projects covering clustering techniques.

The courses were quite insightful. I really liked the case studies. The Avocado case study seemed repeated and wasn't unique like the others. Similarly, the first NLP case study lacked explanation and could have been better. Overall, I recommend this course to those who want to forge their part into the domain of ML and DL.

Course content was SUPER as I have taken courses taught by this team before. a and expected no less. High course challenge for me is the high number of unanswered questions (still remaining) and the time span within which questions are responded to. In particular, I am highly challenged when I cannot proceed: installation issues. Sometimes simply referring to other resources might forge and compile more questions. For me, I blend the course introduction with its practical offers along the journey with high hopes that these will converge.

This course is perfect for students who have the basic knowledge of Python and Machine Learning and wish to apply it in Real World Projects. Each Project is a new challenge and the knowledge and explanation of Prof. Ryan Ahmed is very much appreciative. Each and every concept, step is explained amazingly with examples. Had a great time learning and completing each project and course. Cheers! Happy Learning!

A very good course on a range of Machine Learning techniques. I enjoyed the variety of case studies and was pleasantly surprised with the detailed walk thoughts of each workbook. Machine Learning is a vast topic so don't expect to become an expert in all of the areas discussed such as Neural Netrworks, CNNs and NLP, however this course will give you a solid practical foundation. Highly recommend this course, if you have no knowledge of Machine Learning you may struggle to understand some of the theory but that said, I believe you will still gain solid practical knowledge.

You have given me a clearer understanding of the course material. You are one of the best instructors of all of the courses that I have taken. I place you at the very top of my list. I now have the understanding that I have been seeking and can use this as a key component in the applications that I am developing. Many thanks for the transfer of knowledge. Again Dr. Ryan you are the best.

It has been a very good course to understand the base of very interesting topics on Data Science. Dr. Ryan has explained with good detail the projects scope, theory, how the python code works and gives chance to put in practice the topics learned. Recommend for students with basic to intermediate knowledge on python 3, jupyter notebooks, anaconda, and willing to increase experience with machine learning and deep learning with libraries like tensorflow and keras.

Learning a lot!

Instructor simply explains complex concepts