Python Open Source Projects

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Python Open Source Projects

     Python Open Source Projects gives 100% guaranteed solution for all your needs. Python is an interactive programming language which incorporates exceptions, modules, and very high level dynamic classes and data types. We accomplished 1000+ Python Open Source Projects for students and research fellows in various research domains including Hadoop, Medical Image Processing, Mobile Computing, LTE, MANET, Multimedia, Neural Networks, P2P Live Streaming, Mobile Networking, Remote sensing etc.

Now, we make a list of concepts in Application based and Research based,

First, you can see the application based projects,

  • Social network analysis and geocoding

           -Geocoding a business customer database

           -Social interaction recording

           -Community social network reconstruction

  • Healthcare analysis

           -Mobile data analysis to infer the source and spread  of diseases

           -Smartphone access to the health record

           -Electronic immunization and data analysis

  • Financial inclusion

          -Spatiotemporal data indices construction from big data

         -Geospatial data analysis

          -Market intelligence and analysis

  • Traffic Congestion Analysis
  • Advanced Cognitive Applications
  • Machine Learning Intelligence Approach
  • Renewable Energy and Data Science Approach
  • Pollution Analysis
  • Mobile App and Analysis Dealing

Research based Concepts:

  1. Deep Learning and Cognitive Computing
  2. Advanced Machine Intelligence:
  • Recurrent Neural Networks
  • Unsupervised Learning
  • Evolutionary Computation
  • Integration of Reinforcement Learning and Control principles
  • Probabilistic Graphical Models
  • Knowledge Representation
  • Topological based Analysis
  • Attention Models
  1. Brain Computer Interfaces:
  • Games development
  • Mobile technologies
  • Augmented or virtual reality
  • 3D printed headsets design
  • Active control of robotic devices

/* Sample Python Code for Brain Computer Interfaces*/

# import header files

import numpy as np

import scipy as sp

from scipy.io import loadmat

from matplotlib import pyplot as plt

import matplotlib as mpl

from wyrm import processing as proc

from wyrm.types import Data

from wyrm import plot

from wyrm.io import load_bcicomp3_ds1

plot.beautify()

DATA_DIR = ‘data/BCI_COMP_III_Tuebingen/’

TRUE_LABELS = ‘data/BCI_COMP_III_Tuebingen/true_labels.txt’

# Load test and training data

dat_train, dat_test = load_bcicomp3_ds1(DATA_DIR)

# Load true labels

true_labels = np.loadtxt(TRUE_LABELS).astype(‘int’)

# map labels -1 -> 0

true_labels[true_labels == -1] = 0

def plot_csp_pattern(a):

# Get symmetric min/max values for the color bar from first and last column of the pattern

maxv = np.max(np.abs(a[:, [0, -1]]))

minv = -maxv

im_args = {‘interpolation’ : ‘None’,

‘vmin’ : minv,

‘vmax’ : maxv

}

# Plot

ax1 = plt.subplot2grid((1,11), (0,0), colspan=5)

ax2 = plt.subplot2grid((1,11), (0,5), colspan=5)

ax3 = plt.subplot2grid((1,11), (0,10))

ax1.imshow(a[:, 0].reshape(8, 8), **im_args)

ax1.set_title(‘Pinky’)

ax = ax2.imshow(a[:, -1].reshape(8, 8), **im_args)

ax2.set_title(‘Tongue’)

plt.colorbar(ax, cax=ax3)

plt.tight_layout()

Let’s look at some brain computer interfaces topics using Python,

  • An effective mechanism for Independent component analysis by motor imagery brain computer interface
  • A new technique for Augmenting group performance in target-face recognition by collaborative brain-computer interfaces of surveillance applications
  • A novel study of Brain-computer interface combining eye saccade two-electrode EEG signals and voice cues into improve maneuverability for wheelchair
  • An efficient mechanism for High performance into brain-computer interface control for an avatar using the missing hand representation of long term amputees
  • A new mechanism for Optimal bandpower estimation and tracking by Kalman filtering in real-time Brain-Computer Interfaces
  • A novel study of Prediction for consciousness recovery in patients with disorder with consciousness using Brain-computer Interface
  • An effective performance for simplified hybrid EEG-fNIRS Brain-Computer Interface by motor task classification
  • A novel technique of Effects for illumination and noise based on the performance in P300 brain-computer interface by assistive vehicles
  • An efficient mechanism for Improving in P300-based on brain-computer interface by transfer learning
  • An efficient usage of Minimally invasive brain computer interface by fast typing

 

       In above, we pointed out Brain Computer Interfaces based research topics. Now, we underlined our other marvelous services including web development training (HTML, Java Script, CSS, AJAX, JQM, JQuery, and PHP with MySQL), DOTNET project development training (VB.Net, C#.Net and ASP.NET). We welcome you to become as an expert in your future.