Artificial Neural Networks Jobs

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Fixed-Price - Intermediate ($$) - Est. Budget: $250 - Posted
Here is a nice tool that I used https://github.com/dansoutner/LSTMLM but it is missing some features: 1. It has --ngram parameter that changes results of this program in accordance with some other ARPA LM. I need to have a parameter to reverse it. So that the ARPA file is modified (rescored) in accordante to this program results. 2. I use --ngram parameter like that: python lstmlm.py --initmodel modele/ClaLM.LSTMLM.med.4.lstm --ppl modele/ClaTest.pl --ngram modele/ClaLM.lm.1 0.2 to do the evaluation. All is good but If I want to save combined models with command: python lstmlm.py --initmodel modele/ClaLM.LSTMLM.med.4.lstm --ppl modele/ClaTest.pl --ngram modele/ClaLM.lm.1 0.2 --save-net modele/combined.lstm the program does not save anything. 3. (NOT OBLIGATORY) If it works on GPU and I supply large model that exeeds GPU memory program crashes with: Traceback (most recent call last): File "lstmlm.py", line 937, in <module> lstmlm = LSTMLM(args) File "lstmlm.py", line 221, in __init__ self.model.to_gpu() File "/lib/python2.7/site-packages/chainer/link.py", line 479, in to_gpu d[name].to_gpu() File "/lib/python2.7/site-packages/chainer/link.py", line 479, in to_gpu d[name].to_gpu() File "/lib/python2.7/site-packages/chainer/link.py", line 226, in to_gpu d[name].to_gpu() File "/lib/python2.7/site-packages/chainer/variable.py", line 210, in to_gpu self._grad = cuda.to_gpu(self._grad) File "/lib/python2.7/site-packages/chainer/cuda.py", line 217, in to_gpu return cupy.asarray(array) File "/lib/python2.7/site-packages/cupy/creation/from_data.py", line 47, in asarray return cupy.array(a, dtype=dtype, copy=False) File "/lib/python2.7/site-packages/cupy/creation/from_data.py", line 27, in array return core.array(obj, dtype, copy, ndmin) File "cupy/core/core.pyx", line 1400, in cupy.core.core.array (cupy/core/core.cpp:49505) File "cupy/core/core.pyx", line 1419, in cupy.core.core.array (cupy/core/core.cpp:49263) File "cupy/core/core.pyx", line 87, in cupy.core.core.ndarray.__init__ (cupy/core/core.cpp:5019) File "cupy/cuda/memory.pyx", line 275, in cupy.cuda.memory.alloc (cupy/cuda/memory.cpp:5517) File "cupy/cuda/memory.pyx", line 414, in cupy.cuda.memory.MemoryPool.malloc (cupy/cuda/memory.cpp:8078) File "cupy/cuda/memory.pyx", line 430, in cupy.cuda.memory.MemoryPool.malloc (cupy/cuda/memory.cpp:8004) File "cupy/cuda/memory.pyx", line 337, in cupy.cuda.memory.SingleDeviceMemoryPool.malloc (cupy/cuda/memory.cpp:6972) File "cupy/cuda/memory.pyx", line 357, in cupy.cuda.memory.SingleDeviceMemoryPool.malloc (cupy/cuda/memory.cpp:6799) File "cupy/cuda/memory.pyx", line 255, in cupy.cuda.memory._malloc (cupy/cuda/memory.cpp:5459) File "cupy/cuda/memory.pyx", line 256, in cupy.cuda.memory._malloc (cupy/cuda/memory.cpp:5380) File "cupy/cuda/memory.pyx", line 31, in cupy.cuda.memory.Memory.__init__ (cupy/cuda/memory.cpp:1542) File "cupy/cuda/runtime.pyx", line 181, in cupy.cuda.runtime.malloc (cupy/cuda/runtime.cpp:3065) File "cupy/cuda/runtime.pyx", line 111, in cupy.cuda.runtime.check_status (cupy/cuda/runtime.cpp:1980) cupy.cuda.runtime.CUDARuntimeError: cudaErrorMemoryAllocation: out of memory So here I got a question if this can be easily solved ? If you cannot solve the last one please place your bit with comment that without task 3.
Skills: Artificial Neural Networks CUDA Deep Neural Networks Linux System Administration
Fixed-Price - Expert ($$$) - Est. Budget: $200 - Posted
Hybrid Evolutionary computing neural network based adaptive controlled smes for renewable energy generation system....I want a full execution in MATLAB with the output where we will use Genetic Algorithm for controlling of Superconducting Magnetic Energy storage system for renewable energy system....
Skills: Artificial Neural Networks
Hourly - Intermediate ($$) - Est. Time: More than 6 months, 10-30 hrs/week - Posted
Hello, thank you for the interest in our project. We would like to begin experimenting with LSTM systems to create unique stories. If you heard about the SciFi script, Sunspring, that was brought to life by Thomas Middleditch, that is a perfect example. The end goal would be to be able to output stories that are 15-30 minutes long and totally readable. We expect them to be odd and possibly ridiculous but that is ok as long as someone can get through the whole thing. If you are interested in the projects and would like to chat please feel free to send a message. Please note we are flexible on the budget. We can talk about that when we chat. Thank you.
Skills: Artificial Neural Networks Machine learning
Fixed-Price - Entry Level ($) - Est. Budget: $350 - Posted
I am looking for a person that will guide me how to train from plain text so called: 1. semantic langauge model http://cmusphinx.sourceforge.net/wiki/semanticlanguagemodel I am familiar with tools like SRILM, IRSTLM or KENLM but till now I trained only normal models. I need guidance how train semantic LM from normal textual data like http://opus.lingfil.uu.se/OpenSubtitles2016.php Data pre-processing also should be included in the guide. The resulting model should be in ARPA format if possible
Skills: Artificial Neural Networks Artificial Intelligence Linux System Administration Machine learning
Hourly - Expert ($$$) - Est. Time: 1 to 3 months, 10-30 hrs/week - Posted
I am looking for an expert in using deep learning to help setup some test problems on a mac (single CPU). I have a very large data set for some image and feature classification problems and would like to test out some open-source solutions. I would like to budget about 40 hours spread over a few weeks. While I am open to your suggestions, I am considering testing TensorFlow, Caffe, and Dato/Turi software. Obviously, the more experience you have with these and other packages, the more likely we’ll be a match. Much larger projects (e.g., 20M+ record datasets) may be started once we’ve completed some proof-of-concept projects.
Skills: Artificial Neural Networks Analytics Artificial Intelligence
Fixed-Price - Expert ($$$) - Est. Budget: $6 - Posted
looking for an expert with proven track of profession to create 10-15 slide presentation explaining and illustrating latest technologies in: 1: Facial recognition and emotional sensing 2: news and social media analysis (sentiment analysis) the presentation should include the following: current applications and success stories old technologies, current ones and how new solutions is competing with them or surpassing them the team required to develop these solutions Arabic support and other language support, (English Urdu, etc) accuracy and reliability
Skills: Artificial Neural Networks Machine learning Social Media Optimization (SMO)
Fixed-Price - Expert ($$$) - Est. Budget: $500 - Posted
We are looking for an experienced developer in speech recognition to set up a server for speech transcription (we will provide a virtual machine in the cloud). We will need to pass via web services to the server an .mp3 file and the server will return the trancription in text, XML, SRT or CTM format. Languages needed are english british, english america, spanish (spain), italian and spanish latin america. Ability to add additional languages will be a plus. Candidate will need to document the setting of the server components for troubleshooting and operations. OS preferred are Centos or Windows. Please do not apply if you have not done this before or if you have no idea on how to deliver this in a timely matter. To apply please write in the Cover "I know how to transcribe automatically". You will also need to describe what technology you pretend to use for the server (ie: deep learning, neural networks, etc) and how long it will take for you the setup and preparation to deliver the server.
Skills: Artificial Neural Networks Artificial Intelligence Interactive Voice Response Machine learning
Fixed-Price - Expert ($$$) - Est. Budget: $500 - Posted
We are searching someone to write a neural network algorithm to predict the outcome of our output. Also another algorithm to find anomalies with in the data. This neural network algorithm should also help us do the following: - Analysis per: parameter(feature) vs. prediction to see the relationship between each parameter (feature). - Normalize the feature if needed - The hidden layers is configurable (Default =5) - Teta is initialize randomly but also able to be configured - Snapshot of predicted vs. actual (one month). - To print some results(e.g. mean absolute error The anomalies algorithm should be able to indicate if the data do not conform with to the expected results. Both scripts should be written in R (ONLY!) not using weka. Both scripts should be able to support to csv data formats. Both scripts should be able to support different features names and output names(Output names can be configurable). The bidder should provide the experience he have with neural network and what kind of projects he did.
Skills: Artificial Neural Networks Analytics Machine learning R