constantinembufung
Senior Data scientist with 6+ years of experience in project work, company work, and freelance jobs. Skilled in machine learning, Deep Learning, R, Python
CM Media Douala Cameroun
Pinned Repositories
-100DaysOfMLCode-OCR-Invoice-Recognition
In 100 days i will an OCR invoice recognition software
lstm_image_caption
Applications of LSTM - Image caption Generation. For generating captions for images, we will use a popular dataset for image captioning tasks known as Microsoft Common Objects in Context (MS-COCO). We will �rst process images from the dataset (MS-COCO) to obtain an encoding of the images with a pretrained Convolutional Neural Network (CNN), which is already good at classifying images. The CNN will take a �xed-size image as the input and output the class the image belongs to (for example, cat, dog, bus, and tree). Using this CNN, we can obtain compressed encoded vectors describing images. Then we will process the captions of the images to learn the word embeddings of the words found in captions. We can also use pretrained word vectors for this task. Finally, having obtained both the image and word encodings, we will feed them into an LSTM and train it on the images and their respective captions.
multiclass-classification-with-tensorflow
Neural-Network-on-MNIST-dataset
Lets implement a neural network that is able to classify digits. For this task, we will be using the famous MNIST dataset made available at http://yann.lecun.com/exdb/mnist/
Webscraping-using-python-and-BeutifulSoup
To automate data extraction from a web page into Excel: I have explained the idea on how to automate a data extraction from a web page to Excel using Python. Libraries - Urllib, BeautifulSoup
-First-Steps-with-TensorFlow
First Steps with TensorFlow
Business-Intelligence-with-Power-BI
Go from absolute beginner in Power BI to getting hired as a confident and effective Analyst. Learn Power BI (+ much more) by analyzing real-world datasets and building enterprise-level projects.
ClinicalCodes
An online clinical codes repository to improve validity and reproducability of medical database research
CNN-classifier-for-cats-and-dogs
Building a convolutional neural network with tensorflow to classify cats and dogs
CNN-with-deep-learning-Tensorflow
building a convolutional neural network with tensorflow on the MNIST dataset
constantinembufung's Repositories
constantinembufung/Deep_learning_with_TensorFlow_Keras
In this tutorial series, we will learn the basics of TensorFlow, neural networks and deep learning: We will learn: What is Tensorflow and keras An intriduction to neural networks what the perception and multi-perception are real world examples: handwritten digits recognition
constantinembufung/constantinembufung
Config files for my GitHub profile.
constantinembufung/Telecom-Customers-Churn-Prediction
constantinembufung/complete-data-science-machine-learning-with-pytorch
I will teach you step by step on to build machine learning model using pytorch
constantinembufung/Data-Analysis-with-Python
# Data Analyis with Python Python is a great lanague for doing data analysis. Python have fantastic packages sucha s Pandas, Numpy and Matplotlib that give you a single place to analyse data and do visualization. We'll use Pandas to analyze data on video game reviews from IGN one of the most popular video review site. We are going to use Python 3.5 and google colab running jupyter notebook 4 # Import Data with Pandas our file is a csv file, comma-separated values
constantinembufung/Webscraping-using-python-and-BeutifulSoup
To automate data extraction from a web page into Excel: I have explained the idea on how to automate a data extraction from a web page to Excel using Python. Libraries - Urllib, BeautifulSoup
constantinembufung/Business-Intelligence-with-Power-BI
Go from absolute beginner in Power BI to getting hired as a confident and effective Analyst. Learn Power BI (+ much more) by analyzing real-world datasets and building enterprise-level projects.
constantinembufung/CNN-classifier-for-cats-and-dogs
Building a convolutional neural network with tensorflow to classify cats and dogs
constantinembufung/Titanic-Data-Analysis-with-python
Titanic Data Analysis with python
constantinembufung/iDOTA
iDOTA is AI-based retinal screening application that is developed at the Douala School of AI Research Lab(DSAIRLab) to easily diagnose and prevent blindness in Cameroon. According to the WHO, the number of people of all ages visually impaired is estimated to be 285 million, of whom 39 million are blind. People 50 years and older are 82% of all blind. The major causes of visual impairment are uncorrected refractive errors (43%) and cataract (33%); the first cause of blindness is cataract (51%).
constantinembufung/test
This is test for a new project
constantinembufung/deep_learning_with_keras
constantinembufung/-100DaysOfMLCode-OCR-Invoice-Recognition
In 100 days i will an OCR invoice recognition software
constantinembufung/wp-bootstrap-navwalker
A custom WordPress nav walker class to fully implement the Twitter Bootstrap 4.0+ navigation style (v3-branch available for Bootstrap 3) in a custom theme using the WordPress built in menu manager.
constantinembufung/lstm_image_caption
Applications of LSTM - Image caption Generation. For generating captions for images, we will use a popular dataset for image captioning tasks known as Microsoft Common Objects in Context (MS-COCO). We will �rst process images from the dataset (MS-COCO) to obtain an encoding of the images with a pretrained Convolutional Neural Network (CNN), which is already good at classifying images. The CNN will take a �xed-size image as the input and output the class the image belongs to (for example, cat, dog, bus, and tree). Using this CNN, we can obtain compressed encoded vectors describing images. Then we will process the captions of the images to learn the word embeddings of the words found in captions. We can also use pretrained word vectors for this task. Finally, having obtained both the image and word encodings, we will feed them into an LSTM and train it on the images and their respective captions.
constantinembufung/text-generation-using-neural-network-lstm
we going to used LSTM for text generation. Credit to Thushan Ganegedara. You can read his book on packt.com on NLP using Tensorflow
constantinembufung/mysql-country-list
mysql insert country list into database
constantinembufung/Word-Embeddings
Implementing skip-gram with TensorFlow
constantinembufung/Neural-Network-on-MNIST-dataset
Lets implement a neural network that is able to classify digits. For this task, we will be using the famous MNIST dataset made available at http://yann.lecun.com/exdb/mnist/
constantinembufung/Webscraping-using-python---BeutifulSoup
To automate data extraction from a web page into Excel: I have explained the idea on how to automate a data extraction from a web page to Excel using Python. Libraries - Urllib, BeautifulSoup
constantinembufung/Live-Loss-Plot-example
Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! A live training loss plot in Jupyter Notebook for Keras, PyTorch and other frameworks. An open source Python package by Piotr Migdał et al. When used with Keras, Live Loss Plot is a simple callback function.
constantinembufung/Predicting-Customer-Churn
A common problem across businesses in many industries is that of customer churn. Businesses often have to invest substantial amounts attracting new clients, so every time a client leaves it represents a significant investment lost. Both time and effort then need to be channelled into replacing them. Being able to predict when a client is likely to leave and offer them incentives to stay can offer huge savings to a business. This is the essence of customer churn prediction; how can we quantify if and when a customer is likely to churn?
constantinembufung/python-for-finance-and-backtesting
constantinembufung/multiclass-classification-with-tensorflow
constantinembufung/python-for-finance
Today i am starting a tutorial on using python for finance- we are going to pull stock data from yahoo finance and do data analysis and backtesting using zipline
constantinembufung/CNN-with-deep-learning-Tensorflow
building a convolutional neural network with tensorflow on the MNIST dataset
constantinembufung/Movie-Reviews-with-Deep-Learning-Tensorflow
Movie Reviews with Deep Learning Tensorflow
constantinembufung/-First-Steps-with-TensorFlow
First Steps with TensorFlow
constantinembufung/spark
Mirror of Apache Spark
constantinembufung/R
Some applications about R Programmig Language