- Filter by
- Categories
- Tags
- Authors
- Show all
- All
- Apache Kafka
- Artificial Intelligence
- Big Data
- Cassandra
- Computer Vision
- Data Engineering
- Data Science
- Database
- Deep Learning
- Design Pattern
- DevOps
- Django
- Docker
- ELK
- English
- Feature Engineering
- Finance
- Java
- Java Script
- Keras
- Linear Algebra
- Linux
- Machine Learning
- Mathematics
- MLOps
- NLP
- Python
- PyTorch
- Recommendation Systems
- Reinforcement Learning
- Research
- Software Engineering
- Spark
- State of the art technologies
- Statistics and Probability
- Tensorflow
- Time Series
- Uncategorized
- All
- Apache Kafka
- Big Data
- boltzman
- broadcasting
- Cython
- Deploy
- Django
- Docker
- Elasticsearch
- ELK
- Exception Handling
- Feature Engineering
- GPU
- GRU
- Linux
- Logging
- lstm
- MinIO
- monte carlo
- numpy
- Pandas
- PySpark
- Python
- PyTorch
- Reinforcement Learning
- remover
- S3
- scikit-learn
- Self-Driving Car
- separator
- sklearn
- tmux
- transfer learning
- Tutorial
- Ubuntu
- vocal
2021-02-19
5 mins read Data does not come in a usable format by default; a data science professional has to spend 70–80% of their […]
2021-02-15
Categories
16 mins read Intro and motivation In this post, I would like to describe in detail our setup and development environment (hardware and […]
2021-02-13
Categories
18 mins read Testing your code brings a wide variety of benefits. It increases your confidence that the code behaves as you expect and […]
2021-02-08
Categories
14 mins read Maximum Likelihood Estimation (MLE) and Maximum A Posteriori (MAP) estimation are methods of estimating parameters of statistical models. Despite a […]
2021-02-04
13 mins read In today’s post, we will explain a certain algorithm for matrix factorization models for recommender systems which goes by the […]
2020-12-18
9 mins read Every data mining task has the problem of parameters. Every parameter influences the algorithm in specific ways. DBSCAN (Density-Based Spatial […]
2020-11-24
20 mins read INTRODUCTION The number of research publications on deep learning-based recommendation systems has increased exponentially in the past recent years. In […]
2020-11-20
3 mins read In this post, I’m gonna describe the steps I used to utilize GPU for the PyTorch Deep Learning framework on […]
2020-11-18
8 mins read These notes are taken from the first two weeks of the Convolutional Neural Networks course (part of Deep Learning specialization) by Andrew Ng […]
2020-11-14
10 mins read In the following sections, we are going to implement linear regression in a step-by-step fashion using just Python and NumPy. We will […]
2020-11-13
10 mins read In this article, we are going to implement the most commonly used Classification algorithm called Logistic Regression. First, we will […]
2020-11-09
16 mins read Table of Content: Definition & Structure Reconstructions Probability Distributions Code Sample: Stacked RBMS Parameters & k Continuous RBMs Next Steps […]
2020-11-08
12 mins read The NumPy package is the workhorse of data analysis, machine learning, and scientific computing in the python ecosystem. It vastly simplifies manipulating […]
2020-11-05
A tutorial on the basics of Collaborative Filtering based Recommendations with Python implementation
29 mins read Collaborative Filtering is the most common technique used when it comes to building intelligent recommender systems that can learn to […]
2020-10-15
Categories
6 mins read Linux and Unix administrators usually prefer to work from a terminal. Hence to manage different tasks, the administrator has to […]
2020-10-14
Categories
13 mins read Is your VirtualBox virtual machine starting to run out of disk space? No worries, because VirtualBox allows you to easily […]
2020-07-24
12 mins read Image classification is a subset of machine learning that categorizes a group of images into labeled classes. We train an […]
2020-07-15
9 mins read Whenever you are using a Statistical, Econometrical, or Machine Learning model, no matter how simple the model is, you should […]
2020-07-13
17 mins read Neural networks can do a lot of different tasks. Whether it’s classifying data, like grouping pictures of animals into cats […]
2020-07-13
8 mins read Cross-entropy is a commonly used loss function for classification tasks. Let’s see why and where to use it. We’ll start with […]