deeplearning-notes VS Recognizing_Hand_Written_Digits

If you want in-depth understanding then I would recommend you to look for Deep Learning Specialization by Andrew Ng. (Course 4). He explained the LSTM and GRU cells in detail (mathematically). You can also find it on YouTube I guess. Hope it helps.

Best place to get started https://www.coursera.org/specializations/deep-learning

I want to expand on what I learnt theory and practice to be able to complete a project, where I can download a video and run it through my model and it will be able highlight specified items, e.g people trees, cars. Will this course help me get there https://www.coursera.org/specializations/deep-learning

Another one from DeepLearning.ai and this is also the most popular course for Deep Learning and Neural Networks - https://www.coursera.org/specializations/deep-learning

This course is a part of one of the 5 courses in DL specialization: https://www.coursera.org/specializations/deep-learning. I am taking this course on Coursera where I have finished up to week 2. Now I need to practice for it, but I think I can't access assignments as its locked for paid viewers. Can someone share me the resources for practice or any alternatives you found useful?

There is another [course] (https://www.coursera.org/specializations/deep-learning) by deeplearning ai that catched my eye and in review they say its more in detail than tf in practice course.

Deep learning like others said, but I've seen some posts recommending taking an external class, like Andrew Ng's Coursera class https://www.coursera.org/specializations/deep-learning over the GT one. I haven't taken or plan on taking the GT one but some people found it lacking

My recommendations are worth little, I'm just starting through all this stuff myself. I'm currently taking the Deep Learning specialization on Coursera and trying to map out what else I should be doing.

HR Analytics Employee Retention using Logistic Regression Breast Cancer Classification using Decision Trees Cleaning Student Profile Data Preprocessing and Cleaning Stroke Data Recognizing Hand Written Digits using PCA and SVM techniques Clustering Credit Card Data using Gaussian Mixtures and PCA Clustering Geo-Locations using K-Means clustering Using Numpy and Matplotlib for Image Processing Data Visualization of Australian Wildfires Comparing the classification algorithms for Mushroom Classification Comparing the classification algorithms for Credit Card Frauds Data Visualization and Comparing the classification algorithms for Household Electricity Consumption Data Visualization and Comparing the classification algorithms for grades of Maths and Portuguese class students