Robolab Technologies Pvt. Ltd. | RoboLab Technologies blogs
ROBOLAB ROBOLAB “A perfect platform to explore, learn and build robots” -Advanced state of the art technical research facility within campus -Hands on practical experience along with required theory -Consolidation of concepts -Industry- institute Interaction -Standard guidelines and essentials -Superior quality and Advanced robot study platforms -Training by Industry Experts And last but not the least -Affordable excellence with Quick Return on Investment Robolab is your very own, on campus, centre of Excellence in Robotics and Industrial Automation, tailor made for you. Equipped with all the advanced technologies used in industries, the Robolab offers training courses consistent with the latest curricula and the industry requirements. Thus, functioning as the perfect platform for its users (students as well as teachers) to explore, learn, build and share their ideas. We believe in providing innovative and interactive training by industry experts and deliver the same while establishing the Robolab. This empowers the trainees to manage the Robolab in future. Our planned ROI model ensures the educational as well as financial returns. Having Robolab has its own perks! We have some standard Robolab offerings and we also customize as per the needs of the institute. About Company Robolab Technologies Pvt. Ltd is a venture by graduates from the prestigious College of Engineering, Pune (COEP) in association with the BHAU Institute of Innovation, Entrepreneurship and Leadership (BIEL), the Incubation centre of the College of Engineering Pune[COEP]. Robotics labs for schools in india,Robotics labs for Diploma Colleges in india,Robotics labs for engineering Colleges in india,Robotics labs for colleges in india,a College Of Engineering, Bhau Institute, ,automation and robotics,robotics and automation,automation robotics,robotics automation,robotics & automation,automation robots,automation robotics,automation in robotics,robots and automation,automation and robots,robots in automation,robotics in automation,home robots,home robotics,robots for the home,robots for home,in home robots,learning robotics,lab robotics,learning robots,lab robots,working of robots,college robotics,robotics info,work robots,working of robotics,working in robotics,robots that work,robots learning,training robots,robotics subject,robotics working,lab automation,automation lab,roboti cs,robolab technologies,college from home,mobile education india,robotics workshops training,members of faculty,india private limited,education-india.in,labs in college,the lab training,email id of students,robotics labs india,,robotics lab manual,robotics lab for schools,robotics lab equipment,robotics lab mit,robotics lab setup proposal,robotics lab iit,robotics lab iisc,robotics lab research academy The team Provides services for Robotics Automation laboratories and establishment, trainer kits, laboratory trainer kits, education trainer kits, training equipments, microprocessor embedded trainers, conduct workshops on trending technologies, Industrial Projects. 1.Robotics and Automation Laboratories Establishment 2.Conduct Workshop on Trending technologies 3.Industrial Automation 4.Technical Guidance
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12 Dec
0

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

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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.  

12 Dec
0

Deepy Installation

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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.  

12 Dec
0

Keras based upon the tensor flow

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Keras is an open source neural network library written in Python. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, or Theano. Designed to enable fast experimentation with deep neural networks, it focuses on being user-friendly, modular, and extensible. It was developed as part of the research effort of project ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System), and its primary author and maintainer is François Chollet, a Google engineer.  

12 Dec
0

PyML

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PyML is an interactive object oriented framework for machine learning written in Python. PyML is focused on kernel-methods for classification and regression, including Support Vector Machines (SVM). It provides tools for feature selection, model selection, syntax for combining classifiers and methods for assessing classifier performance.  

12 Dec
0

Pylearn 2 part4

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Pylearn2 is a machine learning library. Most of its functionality is built on top of Theano. This means you can write Pylearn2 plugins (new models, algorithms, etc) using mathematical expressions, and Theano will optimize and stabilize those expressions for you, and compile them to a backend of your choice (CPU or GPU).  

12 Dec
0

Pylearn 2 part3

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Pylearn2 is a machine learning library. Most of its functionality is built on top of Theano. This means you can write Pylearn2 plugins (new models, algorithms, etc) using mathematical expressions, and Theano will optimize and stabilize those expressions for you, and compile them to a backend of your choice (CPU or GPU).  

12 Dec
0

pylearn2 part2

In Artificial Intelligence | No comment

Pylearn2 is a machine learning library. Most of its functionality is built on top of Theano. This means you can write Pylearn2 plugins (new models, algorithms, etc) using mathematical expressions, and Theano will optimize and stabilize those expressions for you, and compile them to a backend of your choice (CPU or GPU).  

12 Dec
0

Pylearn2 part1

In Artificial Intelligence | No comment

Pylearn2 is a machine learning library. Most of its functionality is built on top of Theano. This means you can write Pylearn2 plugins (new models, algorithms, etc) using mathematical expressions, and Theano will optimize and stabilize those expressions for you, and compile them to a backend of your choice (CPU or GPU).  

12 Dec
0

Tensorflow with CNN

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In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery. CNNs use a variation of multilayer perceptrons designed to require minimal preprocessing. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on their shared-weights architecture and translation invariance characteristics.  

12 Dec
0

Tensorflow Examples

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TensorFlow is an open-source software library for dataflow programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks. It is used for both research and production at Google.‍  

12 Dec
0

Tensorflow study

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TensorFlow is an open-source software library for dataflow programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks. It is used for both research and production at Google.‍  

12 Dec
0

Generative Adversarial Networks | Lecture 13

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Generative adversarial networks (GANs) are a class of artificial intelligence algorithms used in unsupervised machine learning, implemented by a system of two neural networks contesting with each other in a zero-sum game framework. They were introduced by Ian Goodfellow et al. in 2014. This technique can generate photographs that look at least superficially authentic to human observers, having many realistic characteristics (though in tests people can tell real from generated in many cases).  

12 Dec
0

Deep Unsupervised Learning | Lecture 12

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Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses. The most common unsupervised learning method is cluster analysis, which is used for exploratory data analysis to find hidden patterns or grouping in data. The clusters are modeled using a measure of similarity which is defined upon metrics such as Euclidean or probabilistic distance.  

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