Electromagnet

Pandas Tutorial Part 3

Pandas is a Data Analysis library for Python. The tutorials contains the fundamentals and advanced concepts of the pandas library like Series, DataFrame, Groupby functions, Aggregate functions, other commonly used functions, Reading CSV files, Sorting, combining multiple conditions, plotting of the data and working with three different CSV datasets.   Code for all the videos can be downloaded from below link https://github.com/tejalal/pandas-tutorial   Installing Python using Anaconda on Windows https://tejalal.wordpress.com/2018/04/06/install-open-cv-on-windows-using-anaconda/   Installing Python using Anaconda on Linux (Ubuntu) https://tejalal.wordpress.com/2018/04/06/install-open-cv-on-windows-using-anaconda/  

Pandas Tutorial Part 2

Pandas is a Data Analysis library for Python. The tutorials contains the fundamentals and advanced concepts of the pandas library like Series, DataFrame, Groupby functions, Aggregate functions, other commonly used functions, Reading CSV files, Sorting, combining multiple conditions, plotting of the data and working with three different CSV datasets.   Code for all the videos can be downloaded from below link https://github.com/tejalal/pandas-tutorial   Installing Python using Anaconda on Windows https://tejalal.wordpress.com/2018/04/06/install-open-cv-on-windows-using-anaconda/   Installing Python using Anaconda on Linux (Ubuntu) https://tejalal.wordpress.com/2018/04/06/install-open-cv-on-windows-using-anaconda/  

Pandas Tutorial Part 1

Pandas is a Data Analysis library for Python. The tutorials contains the fundamentals and advanced concepts of the pandas library like Series, DataFrame, Groupby functions, Aggregate functions, other commonly used functions, Reading CSV files, Sorting, combining multiple conditions, plotting of the data and working with three different CSV datasets.   Code for all the videos can be downloaded from below link https://github.com/tejalal/pandas-tutorial   Installing Python using Anaconda on Windows https://tejalal.wordpress.com/2018/04/06/install-open-cv-on-windows-using-anaconda/   Installing Python using Anaconda on Linux (Ubuntu) https://tejalal.wordpress.com/2018/04/06/install-open-cv-on-windows-using-anaconda/  

Application of Machine Learning in Civil Engineering

This Video has a few examples of Machine Learning in Civil Engineering specific Sub- subjects with examples of applications already done.  

Zero Shot Learning

Zero-shot learning aims to recognize objects whose instances may not have been seen during training. Zero-Shot Learning is a very new area of research, but it is an unquestionable fact that it has a very high potential and it is one of the leading research topics in Computer Vision.  

Cloud TPU (Tensor Processing Unit)

Defining cloud TPU and running MNIST dataset on Cloud Shell and dispay result on TensorBoard.  

Auto Encoders

Auto Encoders are used for reconstruction of input data that can be image, vectors etc. It is a very trending topic and has many applications like In Removing Watermarks, Constructing blurred Image into Clear Image etc.  

Gym (Reinforcement Learning)

Gym is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents everything from walking to playing games like Pong or Pinball.  

Deep Learning Models in Cloud

This video discusses various methods to train deep learning/machine learning models on cloud at free of cost  

Tutorial on GenSim, a tool for Topic Modelling (Part 1)

Gensim is a robust open-source vector space modeling and topic modeling toolkit implemented in Python. It uses NumPy, SciPy and optionally Cython for performance. Gensim is specifically designed to handle large text collections, using data streaming and efficient incremental algorithms, which differentiates it from most other scientific software packages that only target batch and in-memory processing.  

Tutorial on GenSim, a tool for Topic Modelling (Part 2)

Gensim is a robust open-source vector space modeling and topic modeling toolkit implemented in Python. It uses NumPy, SciPy and optionally Cython for performance. Gensim is specifically designed to handle large text collections, using data streaming and efficient incremental algorithms, which differentiates it from most other scientific software packages that only target batch and in-memory processing.  

Tutorial on GenSim, a tool for Topic Modelling (Part 3)

Gensim is a robust open-source vector space modeling and topic modeling toolkit implemented in Python. It uses NumPy, SciPy and optionally Cython for performance. Gensim is specifically designed to handle large text collections, using data streaming and efficient incremental algorithms, which differentiates it from most other scientific software packages that only target batch and in-memory processing.  

Tutorial on GenSim, a tool for Topic Modelling (Part 4)

Gensim is a robust open-source vector space modeling and topic modeling toolkit implemented in Python. It uses NumPy, SciPy and optionally Cython for performance. Gensim is specifically designed to handle large text collections, using data streaming and efficient incremental algorithms, which differentiates it from most other scientific software packages that only target batch and in-memory processing.  

Nolearn (Machine Learning)

nolearn contains a number of wrappers and abstractions around existing neural network libraries, most notably Lasagne, along with a few machine learning utility modules.  

Understanding a program in Deepy

Deepy is a deep learning framework for designing models with complex architectures. Many important components such as LSTM and Batch Normalization are implemented inside. Although highly flexible, deepy maintains a clean high-level interface.  

Deepy Installation

Deepy is a deep learning framework for designing models with complex architectures. Many important components such as LSTM and Batch Normalization are implemented inside. Although highly flexible, deepy maintains a clean high-level interface.