Deep Learning Bootcamps NYC 2017-11-09T12:17:11+00:00

 Deep Learning Bootcamp

AI Tenser Flow  

Deep Learning Bootcamp| Tensorflow Tutorials

AI – Tensor Flow Deep Learning | Deep Learning Bootcamp

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Deep Learning Bootcamp NYC

Deep Learning Bootcamp

Deep Learning Bootcamp – Objective of the course overall

The objective of this deep learning bootcamp is to provide an introduction to deep learning theory and practical applications using tensorflow.  The deep-learning training focuses on building deep neural network models in tesorflow for typical problems. In this deep learning bootcamp your will receive a full training for using tensorflow, which is the most popular library for building your own neural network. This deep learning bootcamp guarantees you that you will receive all tools end theory needed to work as deep learning engineer from experts in the field.

Deep learning bootcamp is for anyone that wants to make a career in Deep learning  (DL) and Artificial intelligence (AI).  It doesn’t matter if you are a computer scientist or just a creative coder without machine learning background.  In this deep learning bootcamp, it is covered basic fundaments of the state-of-the-art of deep learning, and the basic of tensorflow and python.


In Class: $9,999
Next Session: 25th Nov 2017

   Online: $2,999
   Next Session: On Demand

Home / All courses / Advance Deep learning / Deep Learning Bootcamp | Tensorflow Tutorials

Deep Learning Bootcamp| Tensorflow Tutorials

Instructor: John Doe, Lamar George

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Tensorflow with Image recognition - Deep Learning Bootcamp

Tensorflow with Image Recognition – Deep Learning Bootcamp

Deep learning Bootcamp (DL)

Deep learning is a set of powerful algorithms used in amazing applications such as self-driving cars, image searching, voice recognition, prediction, financial forecast, medical image diagnosis, and many other applications. Actually, many companies need people with deep learning bootcamp in their business processes and data assets to realize the vision of an intelligent enterprise.  However, building learning models and deploying them to enterprise applications requires specialized skills in neural networks and tensorflow (deep learning bootcamp).

The deep-learning technology works by filtering input data through a succession of many data-processing layers. There are many open source and user-friendly deep learning framework that are used to build a deep learning neural network. A deep learning bootcamp plays an important role for every data scientist.

Recent research studies show how psychological profiles of authors can be predicted using deep learning techniques. It was used a convolutional neural network to find patterns of the big five personality traits in various text. This Artificial Intelligence (AI) technology for recognizing patterns in human behavior is creating a new market in the industry. Actually deep learning bootcamp  for data scientists has become very important in the health field for medical diagnostics.

Engineers with Deep learning bootcamp are working in a personality detection problem, which is a very difficult classification task due to the ambiguity of natural language. Actually, using deep leaning it is possible to develop a system that can understand both user’s feelings and intentions. The deep learning system is able to find relevant features form text automatically.  The accuracy of those systems is around 60%.

Recent research studies in deep learning present text-based personality identification using audio and image data to find patterns. This type of deep learning system is capable of understanding speakers’ personalities, sentiments and emotions in multimodal interactions in real time. Many data scientists have a deep learning bootcamp specialized for sentiment analysis.

This type of deep learning is called opinion mining. Companies have a high interest in this type of research because potentially it increases their revenue if they knew what users like and dislike in their products and services because they could modify accordingly. However, this type of system has the disadvantage of wrongly classify the information if the comment for a product is good or bad, due to problems such as sarcasm and tone. A deep learning system for sentiment analysis can clarify the data. The deep learning bootcamp for sentiment and opinion mining is increasing.

Using this deep learning bootcamp, it is possible to create systems to classify Internet users by personality type using the user’s writing.

Actually there are many other applications in other sectors for this technology such as personalized opinion mining, including personalized recommender systems, determination of personality type, selection of personalized learning plan (in education sector), determination of fitness for a particular profession (in human resources management), targeted advertising (in commerce sector), large scale mining for early detection of users with suicidal tendencies in social networks (in health care sector), mining for users with tendencies for terrorist activity (in social security sector), and many other applications of this technology has been used by people with deep learning bootcamp.

Hemnet Home (also known as the “House of Clicks”) uses deep learning to detect the personality of users, and this acquired knowledge is used to design products that they want.

Hemnet, which is a real estate website in Sweden, used big data to design a dream house. The data scientists analyzed over 200 million clicks on Hemnet in order to determine what people like in a home. It was designed a home with those qualities. The project had such much success that hundreds of buyers were interested in purchase the house. Data scientists have deep learning bootcamp for this industrial sector.

Nowadays, a self-driving system that doesn’t require human intervention in most scenarios uses deep learning techniques. is a Silicon Valley startup founded by deep-learning experts from Stanford University’s Artificial Intelligence Laboratory with deep learning bootcamp. Their deep-learning approach of autonomous driving is so strong because they used their deep learning bootcamp to develop a whole autonomous driving system.

The most common implementation of deep learning is for classification. For example, recognizing pedestrians in a camera image using deep learning bootcamp models for classifying things within a random scene.

Another implementation of deep learning techniques is in self-driving, it is possible to find patterns that are used for decision-making and motion planning. In the case of self-driving, deep learning bootcamp models are used to classify the right behavior at a four way stop or to predict when the light is turning right on red.

A deep learning system is an algorithm that receives an input (information or images) and have an output (classification or numeric prediction).  The main function of this deep learning bootcamp model is to recognize patterns. A learning algorithm and neural networks are used to find a pattern in the data (deep learning bootcamp model). Once the system is trained (with training data), data can be fed to the deep learning bootcamp model in order to have a reliable output (classification or prediction) in comparison with other methods as machine learning.

In Deep learning bootcamp, the more data that you feed the system, the better it’ll be able to recognize and generalize about the patterns needed to have a good deep learning bootcamp model to drive safely, classify, or predict.

In the last few years, many enterprises are using deep learning bootcamp people to get better profits, for that they are using real-time data and real-time streaming of unstructured data or binary data. For example, performing speech-to-text recognition of audio files, recognizing individual speakers, and automatically classifying files.

Automatically classifying image files based on the recognized patterns (objects) such as faces, objects, labels, products, and so on. People with specialized deep learning bootcamp in image recognition is needed for many companies like Google.

In the last few years, there are many companies that are using advances in computer vision and deep learning to solve real-world business problems. Deep learning bootcamp in image recognition is very important in the field.

Nowadays, enterprises have people with deep learning bootcamp to apply techniques such as convolutional neural networks for image classification. This network architecture learns image features automatically with better accuracy, which depends on the quality of the data set that must be properly labeled and appropriate for the problem.

There are many types of industries that require people with deep learning bootcamp to work with.  Industries such as insurance, automotive, financial services, media, health care and retail have trained people in deep learning bootcamps to work in specific classification or predictive problems.

In insurance companies such as Orbital Insights, it is used deep learning for analyzing satellite imagery to count cars to predict mall sales, or to count oil tank levels automatically to predict oil production. Insurance companies also use deep learning to analyze the damage on assets. Deep learning bootcamp in image classification is very important in this field.

In the automotive industry, deep learning has been used for many applications such as scene analysis, automated lane detection, automated road sign reading to set speed limits, self-driving cars, and so on.  Besides convolutional neural networks, the automotive industry also uses long-short-term memory networks to analyze sensor data to detect other cars and objects around the car. Actually, on newer cars, if the driver change lanes on the highway without setting the turn signal, the car will automatically directing the car back into the lane. Deep learning bootcamp in image classification is very important to automotive industry.

Uber has people with deep learning bootcamp working in: self-driving cars, image classification, and fraud detection problems.

The media companies are have people with deep learning bootcamp working in image classification problems. For example, media companies are using deep learning to recognize brands on images. For example, Ebay is using deep learning to let user search products with photos. Paypal is using deep learning to block fraudulent payments. Amazon is using deep learning to make product recommendations for users.

Car2go and Uber are using deep learning to predict ride-sharing fleets. They are using LSTM, which means long-short term memory, and temporal information of users to predict ride-sharing fleets. Deep learning bootcamp in LSTM technique is required for succeeding in this field.

Financial services are using deep learning for automatic asset wealth management and prediction. They are using deep learning and reinforcement learning to make predictions.  Actually, many financial services need people taking deep learning bootcamp in forecasting.

In health care industries, there are people with deep learning bootcamp working with classification problems to detect diseases using MRI scans. For example, Arterys Company uses deep learning to model medical imagery data. Actually, Google, Nvidia, and Massachusetts General Hospital have a partnership to develop applications using people with deep learning bootcamp in classification problems to detect patterns on radiology tasks.

IBM and Google have made important investments in the health care sector for developing the deep learning technology. They are using deep learning to early identification of diseases. For example, they are using convolutional neural networks to detect lung cancer. Deep learning bootcamp is indispensable to have a job in these companies.

Retail companies have people with deep learning bootcamp to develop models to analyze the shopping carts and detect items and make recommendations about what else they might want to buy in store. Retail companies are using complex cameras for taking pictures and convolutional neural networks.

Manufacture sector are using LSTM and other deep learning techniques to predict maintenance or energy used.

Artificial Intelligence (AI) is considered the biggest business opportunity in the new economy that is expected to generate $15.7 trillion by 2030. Deep learning is increasingly being used in automotive applications, predicting demand, determining deficiencies around service and product quality, detecting new types of fraud, streaming analytics on data in motion and providing predictive or even prescriptive maintenance. Deep learning bootcamps are increasing due to market.

Most companies are pushing IT leaders to seek specialists in deep learning. Market research firm Gartner predicted that 80% of data scientists would have deep learning bootcamp by 2018.

Actually deep learning bootcamps are training people to apply deep learning to resolve industry problems. The average salary for a deep learning engineer is $149,465 per year.

The deep learning techniques promise to transform whole industries, in fact, that startups see an opportunity to offer deep technical expertise to companies, from financial firms to Web startups. Actually, Google and Facebook have interest in improving deep learning. These companies need people with certificate courses taken in deep learning bootcamps.

Google uses deep learning models to do photo search. Facebook uses deep learning for photo-tagging facial recognition. Smartphones use deep learning for speech recognition. The private sector understands the importance of deep learning bootcamp . Actually, companies like NVIDI, which is a technology company based in Santa Clara, California, just announced plans to train 100,00 developers through its NVIDIA Deep Learning Institute.

Artificial Intelligence (AI) is the biggest business opportunity and it is expected to generate &15.7 trillion by 2030. The growth of the global GDP is of 14%.

The expected productivity gain would be $6.6 trillion. The industries that would produce this productivity gain are: robotics, autonomous vehicles or automated intelligent services. Other companies that are part of this productivity gain are the ones that do business scenario simulations or decision-making support. It is expected that the demand of deep learning would increase from higher quality products which will be more intelligent and better adapted to the specific customer needs.  Actually, 90% of the market of deep learning has been created in the last two years. This means that the companies need people trained in deep learning bootcamps.

Deep learning bootcamps of Bigdaaguys offers qualify courses in deep learning acquire a job as deep learning engineer in industries Google, Facebook, Uber, or any other company. The best way to learn about deep learning is to take a course with us. Deep learning bootcamp covers the basic theory and practical examples to create your own deep learning neural network.


Lecture1.1 NN and RNNLecture1.2

Lecture1.2 Backpropagation

Lecture1.3 Long short-term memory (LSTM)

Lecture2.1 Creation, Initializing, Saving, and Restoring TensorFlow variables

Lecture2.2 Feeding, Reading and Preloading TensorFlow Data

Lecture2.3 How to use TensorFlow infrastructure to train models at scale

Lecture2.4 Visualizing and Evaluating models with TensorBoard

Lecture3.1 1. Prepare the Data Download Inputs and Placeholders

Lecture3.2 2. Build the Graph Inference Loss Training

Lecture3.3 3 Train the Model The Graph The Session Train Loop

Lecture3.4 4 Evaluate the Model Build the Eval Graph Eval Output

Lecture4.1 Threading and Queues

Lecture4.2 Distributed TensorFlow

Lecture4.3 Writing Documentation and Sharing your Model

Lecture4.4 Customizing Data Readers

Lecture4.5 Using GPUs¹

Lecture4.6 Manipulating TensorFlow Model Files

Lecture5.1 Introduction

Lecture5.2 Basic Serving Tutorial

Lecture5.3 Advanced Serving Tutorial

Lecture5.4 Serving Inception Model Tutorial

Online: $3,999
Next Batch: starts from 15th Nov 2017

In Class: $9,999
Locations: New York City, D.C., Bay Area
Next Batch: starts from 25th Nov 2017


Skill level: Intermediate
Language: English
Certificate: No
Assessments: Self
Prerequisites: Basic Python programming






data science Bootcamp
Deep Learning with Tensor Flow In-Class or Online

Good grounding in basic machine learning. Programming skills in any language (ideally Python/R).

Instructors: John Doe, Lamar George
50 hours
Lectures:  25

Neural Networks Fundamentals using Tensor Flow as Example Training (In-Class or Online) 

Good grounding in basic machine learning. Programming skills in any language (ideally Python/R).

Instructors: John Doe, Lamar George
50 hours
Lectures:  25

Deep learning tutorial

Tensor Flow for Image Recognition Bootcamp (In-Class and Online)

Good grounding in basic machine learning. Programming skills in any language (ideally Python/R).

Instructors: John Doe, Lamar George
50 hours
Lectures:  25




Advanced Course like Deep Learning Bootcamp with tensorflow duration largely depends on trainee requirements, it is always recommended to consult one of our advisors for specific course duration.

We record each LIVE class session you undergo through and we will share the recordings of each session/class.

If you have any queries you can contact our 24/7 dedicated support to raise a ticket. We provide you email support and solution to your queries. If the query is not resolved by email we can arrange for a one-on-one session with our trainers.

You will work on real world projects wherein you can apply your knowledge and skills that you acquired through our training. We have multiple projects that thoroughly test your skills and knowledge of various aspect and components making you perfectly industry-ready.

Our Trainers will provide the Environment/Server Access to the students and we ensure practical real-time experience and training by providing all the utilities required for the in-depth understanding of the course.

Yes. All the training sessions are LIVE Online Streaming using either through WebEx or GoToMeeting, thus promoting one-on-one trainer student Interaction.

The  Deep Learning Bootcamp with tensorflow by BigdataGuys will not only increase your CV potential but will offer you a global exposure with enormous growth potential.


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Lab Exercises93
Trainer Quality96




John Doe
Learning Scientist & Master Trainer 
John Doe has been a professional educator
for the past 20 years. He’s taught, tutored,
and coached over 1000 students, and he
holds degrees in Physics and Literature
from Northwestern University. He has
spent the last 4 years studying how
people learn to code and develop applications.

Lamar George
Learning Scientist & Master Trainer 
He has been a professional educator for
the past 20 years. He’s taught, tutored,
and coached over 1000 students, and
he holds degrees in Physics and Literature
from Northwestern University. He has
spentthe last 4 years studying how
people learn to code and develop applications.

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