Most of the times, when attempting to visualize and build deep learning models using real-world data, you usually never get a dataset fiiting your requirement closely. In this case, it becomes necessary to...
Mar 4, 2021
Have you been feeling frustared about the complexity of deep learning terms like Convolutional Neural networks and Recurrent NNs?. So even if you have found it difficult to assimilate, I want to clear out ...
Oct 14, 2020
Are there specific skills important in deep learning?. You shouldn't be surprised if you ask yourself this question. At a time or another, all budding deep learner ask themselves the same question. Are you...
Oct 9, 2020
Can you imagine navigating through an unknown city without Google Maps?It is usually a tough and tiring ordeal, all paths seems to lead to nothing and at the end you even ask yourself why you took that pat...
Sep 21, 2020
Buiding Models is exciting, putting them to use can be very brain-tasking. For people who have mastered model deployment, usually this involves just a few tweaks to the code to make it work for a new probl...
Sep 17, 2020
No doubt, AI is one of the most crucial future technologies which is being harnessed today and transforming our daily lives. A very important branch of Artificial Intelligence "Deep Learning" has arguably ...
Sep 8, 2020
Virtual Reality is a technology that is relatively new in the industry, there exists some skeptisism about it but if we really use our imagination as is required, what does the future hold for us in VR. Th...
Aug 9, 2020
In this tutorial you would see how to apply state-of-the-art R-CNN architecture model built on the MS Coco dataset for Object Detection on a new Dataset. We use Transfer Learning for efficient and faster t...
Jul 24, 2020
In this tutorial we would explore a necessary topic in deep learning - overfitting. We would learn what it is ,and how to combact it using known regularization methods like dropouts, batch normalization et...
Jul 11, 2020
The task of helping computers to see, and make a sense or add meaning to what they see is a very hard task. Mainly because it does not just involve one but a series of steps are involved owning to the fact...
Jun 28, 2020
Using generative models, we first learn the distribution of the training set and then generate some new observations or data points using the learned distribution with some differences.
Jun 22, 2020
Vectorization is the process of converting an algorithm from operating on a single value at a time to operating on a set of values (vector) at once.. In a vectorized calculation, all elements of the vector...
Jun 16, 2020
Linear Regression is a Machine Learning algorithm that is used for predictions of "continuous /non-classified data".You have some datasets in continuous values(because we are doing LinearRegrssion) and you...
May 31, 2020
Machine Learning is a sub-field of Artificial Intelligence. It is the concept that defines the different methods in which a Machine (preferably referred to as model) can learn from real world data and have...
May 17, 2020
When trying to build a high-brew model in image classification, you can solve the problem using different methods, but just few are efficient ways of doing so. In this tutorial we look at how to build a mi...
Feb 15, 2020