Artificial Intelligence

   

LIST OF PRACTICALS for Artificial Intelligence (AI)

Write a programme to conduct uninformed and informed search. Write a programme to conduct game search. Write a programme to construct a Bayesian network from given data. Write a programme to infer from the Bayesian network. Write a programme to run value and policy iteration in a grid world. Write a programme to do reinforcement learning in a grid world. Mini Project work.

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/  

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.  

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.  

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.  

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.  

error: Context Menu disabled!