Okay, so this search engine will not be a full-fledged one but you’ll get a hand wtih all the capabilities of the OpenAI’s CLIP model and how to use it to your own use cases.
In this story we’ll see how you can deploy your tensorflow model on an Android device using Tflite. Ok, but why do you want to run your models on Android ? For fun ? or testing you model on REAL data ?
Well, for me it’s both.
Training a model on laptop using python is a no brainer. Gather data and boom ! Using Pytorch or Tensorflow you can train it pretty easily. But what about putting your model on an Android device.
You have to understand the limitations of putting you model on phone. First you don’t have numpy…
It’s fun to build apps as personal projects, but what if you want it to deploy it and showcase it to others? And not only that it should be able to handle multiple requests simultaneously. Well, in this article we’ll do this. Create Django apps, use PostgreSQL as a database and use Apache2 for handling multiple requests and some tips for logging and debugging errors.
Launch a new Instance on AWS EC2 using the following configs:
Back in 2018, I wrote an article “Django + Angular 4 = A powerful web application” which has over 15k reads. Out of curiosity, I tried Angular 4 and Django. Continuing the series, here is a new article helping you to build amazing apps using - “Vuejs” and “Golang”.
I know, these two aren’t popular to be used along with each other. But, let’s try…
Okay so first, let’s talk about the features these technologies provide.
In the previous part we saw what is Image Processing, how it works and some basics of Matlab/Octave. In this part we’ll see color model, some additional functions in Matlab/Octave and how to do basic image enhancement.
Color model is a mathematical way to represent colors as combination of three or four numbers in a tuple.
Let’s see some of the color models.
RGB (Red Green Blue)
Really ? an AI to play F1 race game ? Well kind of. This story is more over as a helper guide rather than a tutorial to build the whole system.
I started it out as a project as an experiment and built some groundwork which you can further improve by contributing.
So, lets first talk about the game.
You know how to use Django to make web apps and also, you know how to build beautiful frontends using Angular but you were probably wondering how to integrate them with each other to build a single web app that has benefits of both?
This was the thing that was going in my head when I was learning Django and Angular 4. I wanted both of them in the same application so that I would be having the power of python and goodness of Angular and without learning node.js separately to make a full-fledged Web App. …
We saw in the previous article about how to solve the FrozenLake environment available in OpenAI gym toolkit using Q-learning. In this article, we’ll solve it using the SARSA algorithm.
SARSA is an on-policy algorithm where, in the current state, S an action, A is taken and the agent gets a reward, R and ends up in next state, S1 and takes action, A1 in S1. Therefore, the tuple (S, A, R, S1, A1) stands for the acronym SARSA.
In the previous part, we saw what an MDP is and what is Q-learning. Now in this part, we’ll see how to solve a finite MDP using Q-learning and code it.
As stated on the official website of OpenAI gym:
Gym is a toolkit for developing and comparing reinforcement learning algorithms.
Install gym using the steps provided here. First install the gym library then, the OS specific packages.
This is a how-to for using NTFS formatted external HDD on MacOS using free tools available.
MacOS doesn’t provide write permissions on NTFS format as default. So to mount external drives as Read/Write follow the given steps below:
Download FUSE for macOS from here
Then we have to install xcode command line tools. For this open terminal and copy paste this.
Then click install when the dialogue appears. Click Agree when the License Agreement appears. Once that’s done proceed to step 3.
Now we have to install Homebrew which is a package manager for macOS. …
Machine/Deep Learning, Amateur Photographer