Author: moshfiqur

Product Update: Your Movie Expert Chat Buddy

Being a movie freak, I always wanted to have a buddy with whom I can talk about movies or ask question if certain part of any movie is not clear to me. Failing to get a real life movie friend, I decided to develop a chatbot and train it with generic amount of movie info […]

Find movie overview similarity using gensim

I am working on to build a movie recommendation system which will understand my taste for movies and will recommend accordingly. The typical movie recommendation system available now does not work very good for me. I guess it is because they mostly matches the genre of movie I watched and recommend movies from that same […]

Restoring A Trained TensorFlow Model And Predict Using That

So you have trained your first machine learning model using Tensorflow. Now you want to use your model to do prediction of independent data but you don’t know how to do it? The tutorial you were following online ends with lots of evaluation and validation scores and graphs but does not give any hint about […]

Object Detection Using Already Trained Models

In this jupyter notebook, we will try two different model: SSD Mobilenet trained on COCO dataset and Faster RCNN model trained on Resnet dataset. Object Detection using ssd_mobilenet_v2_coco_2018_03_29 and faster_rcnn_inception_resnet_v2_atrous_lowproposals_oid_2018_01_28 We need several utilities from tensorflow/model repo. The repo can be found here. Download the repo and add the path of research and research/object_detection to […]

Processing and Showing Images in Jupyter Notebook

This jupyter notebook shows how to process and showing images. First, load all the necessary modules for image processing. import numpy as np import os import six.moves.urllib as urllib from PIL import Image import cv2 import matplotlib.pyplot as plt %matplotlib inline Here, we define the directories from where the images are loaded. ROOT_DIR = ‘/Users/sparrow/Learning/machine-learning/the-eye’ […]

Handwritten digit recognizer on MNIST

Kaggle competition: Digit Recognizer This notebook implements a hand written digit recognizer trained on MNIST dataset. It was implemented for the kaggle knowledge competition named Digit Recognizer. Import the necessary modules import matplotlib.pyplot as plt import numpy as np import random as ran import tensorflow as tf import os import pandas as pd %matplotlib inline […]

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