DigitalSreeni Courses

Regression Using Neural Networks and Comparison to Other Models

Explore neural network regression, compare with other models, and learn practical implementation using Python for data analysis and prediction.

• YouTube
• 22 minutes
• On-Demand
• Free Video

The Topology of Deep Neural Networks - Designing Your Model

Explore deep neural network topology and model design techniques for effective machine learning implementations.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Data Augmentation Using Keras

Explore image augmentation techniques using Keras, including reshaping and multiclass augmentation, to enhance your deep learning models.

• YouTube
• 20 minutes
• On-Demand
• Free Video

Denoising MRI Images - Also CT & Microscopy Images

Learn effective techniques for denoising MRI, CT, and microscopy images using traditional methods like Gaussian smoothing, bilateral filtering, anisotropic diffusion, non-local means, and BM3D algorithms.

• YouTube
• 43 minutes
• On-Demand
• Free Video

Introduction to Transfer Learning

Explore transfer learning to adapt pre-trained networks for microscopy applications, enhancing accuracy with limited labeled data and reducing training time.

• YouTube
• 21 minutes
• On-Demand
• Free Video

Application of Autoencoders - Image Colorization

Learn to artificially colorize black and white images using autoencoders in Python. Explore the process, implementation, and practical application of this advanced image processing technique.

• YouTube
• 21 minutes
• On-Demand
• Free Video

An Introduction to Autoencoders - In Python

Learn to build and implement autoencoders in Python for image compression, reconstruction, and various applications like denoising and anomaly detection.

• YouTube
• 21 minutes
• On-Demand
• Free Video

How to Build a Docker With Your Code and Run It on APEER

Learn to create and deploy a Docker module on APEER for microscopy and image processing applications, enabling cloud-based workflows and easy integration with other modules.

• YouTube
• 42 minutes
• On-Demand
• Free Video

Malarial Cell Classification Using CNN

Learn to classify malarial cells using CNN in Python. Covers dataset acquisition, TensorFlow setup, network design, and result analysis for detecting parasitized and healthy cells.

• YouTube
• 49 minutes
• On-Demand
• Free Video

An Overview of Deep Learning and Neural Networks

Comprehensive introduction to deep learning concepts, covering neural networks, convolution, pooling, normalization, and more. Includes code examples for practical implementation.

• YouTube
• 34 minutes
• On-Demand
• Free Video

How to Use Random Forest in Python

Learn to implement Random Forest in Python for data analysis, including data importing, feature engineering, and model fitting techniques.

• YouTube
• 32 minutes
• On-Demand
• Free Video

Linear Regression Using Sci-Kit Learn in Python

Learn to implement linear regression using Sci-Kit Learn in Python, from data import to model creation, evaluation, and prediction. Hands-on coding with real-world data.

• YouTube
• 25 minutes
• On-Demand
• Free Video

What Is Machine Learning Anyway?

Explore the fundamentals of machine learning, its applications in microscopy, and different types including supervised and unsupervised learning.

• YouTube
• 21 minutes
• On-Demand
• Free Video

Introduction to Pandas - Data Reading and Handling

Learn to load, manipulate, and analyze data using Pandas in Python. Covers CSV file handling, data types, and basic operations for efficient data processing and analysis.

• YouTube
• 23 minutes
• On-Demand
• Free Video

Grain Size Analysis in Python Using Watershed

Watershed-assisted segmentation in Python for analyzing grain size in microscope images, overcoming limitations of threshold-based methods for improved accuracy in feature separation.

• YouTube
• 39 minutes
• On-Demand
• Free Video