How to practice?

[Samarth_Minocha]

Hi, I am done with the ML specialization course and wanted to practice the concepts I have learned till now before moving forward. Any recommendations for how to go about it? Thanks in advance!

[Deepti_Prasad]

Hello Samarth

Refer this

Please help with course selection

Hello Samarth, Adding to Nydias’ suggestions. As I myself did first DLS course specialisation and during the second course of DLS where Andrew mentions to do TensorFlow course, thereby I continued doing both. If you are planning for any AI app model algorithm then surely doing DLS should be first choice but then what I felt personally when I did TensorFlow, I could understand some of the concept of DLS more properly, So after finishing the first course of DLS, simultaneously please do TensorF…

Regards
DP

[Nydia]

Hi! @Samarth_Minocha Good to hear you are eager to continue! To apply what you have learned so far you could enter into Kaggle competitions.

How?
→ Explore Kaggle datasets: Look for datasets that interest you and align with your ML expertise. Familiarize yourself with the data and its features.
→ Explore kernels and notebooks in Kaggle: Kaggle has a section called “Kernels” where users share their analysis and machine learning solutions. Study the top-performing kernels related to the datasets you’re interested in.
→ Participate in Kaggle competitions: Kaggle hosts ML/DL competitions with real-world datasets and challenging problems (you could also win money when winning a competition!). Participating in these competitions will give you hands-on experience and a chance to learn from experts. Even if you don’t aim for the top position in the ranking, the learning process is invaluable.