Deep Learning with Python “Data Science Training in Pune”

 Deep learning is also known as deep structured learning. It is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised.

Deep learning architectures such as deep neural networks, deep belief networks and recurrent neural networks have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics and drug design, where they have produced results comparable to and in some cases superior to human experts. Data Science Training in Pune is providing advanced training in Data Science.

Deep learning models are vaguely inspired by information processing and communication patterns in biological nervous systems yet have various differences from the structural and functional properties of biological brains, which make them incompatible with neuroscience evidence.

The term Deep Learning was introduced to the machine learning community by Rina Dechter in 1986. Deep learning is closely related to a class of theories of brain development. Deep Learning or Machine learning we can do by any one of the programming languages Like by Python, by R Programming Language or by Spark and Scala. People can create Deep Learning algorithms by using python.

Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow.

Python Training in Pune:

Python is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace. It provides constructs that enable clear programming on both small and large scales.

In Python Institutes in Pune, Lot of modules are there in the market like Core Python, Python Scripting, Python with Data Science, Python in Data Visualization, Python in Machine learning, Python in Deep Learning. Python is the future of the IT Industry. In Python, Technogeeks offers every module of Python like Core python.

Some topics of Core Python which Technogeeks is going to cover are:

• Core Objects and Built-in Functions
• Conditional Statements and Loops
• UDF Functions and Object Functions
• Debugging, Framework & Regular expression
• Exceptional Handing and Object-Oriented
• Python Built-in Library
• File Handling with Python
• Database interaction with Python
• Package Installation, Windows spreadsheet
• Parsing and webpage scrapping

Data Science with Python:

Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, structured or unstructured, similar to data mining.

Data Science Technogeeks offers Machine Learning, Deep Learning, NLP (Natural language processing), Data visualization these concepts Technogeeks providing by Python, R programming language and by Spark & Scala also.

For learning data science any one programming language is required. Python is one of the vast programming languages to learn data science because there is a lot of libraries or you can say bundle of libraries in python. Technogeeks offers Python Training in Pune with 2 Real-time projects and POCs in that Data Science Course total course which Technogeeks offers is provided by Data Scientists only.

Which is the best data science training institute in Pune which can also provide job assistance or placement assistance to candidates?

In general, Data Science covers many topics within its network, including AI, deep learning, IoT, and many others. The action of the data interface and calculation in the algorithm to solve many problems of the enterprise. With the growth of data science and the latest technological advancements, the benefits of data science have multiplied. This will be the scope of data science in 2019.

The Continuing Future of Data Science Considers this type of trend for the coming year. The future of innovation and business can be considered as a large database. Data Science will bring just as much ease of use and development in the coming year. The digital world has increased dramatically.

Technogeeks is the best institution offering Data Science Training in Pune for fresh graduates as well as Working Professional. Technogeeks offers well managed Data Science Course in Pune and also provide 100% placement assistance through its industrial Training division that interfaces with the global giants hiring cloud professionals.

Digital experiences will fully relate to human experiences. This type of trend should be revealed and updated immeasurably. One type of big data analysis focuses on updating business operations. Essentially, they need to understand all of the company's work processes and transfer data to companies. Finally, all of the above concepts will explain the scope of data science in 2019.

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Is data science really a rising career?

A huge amount of data is generated every day by companies. This means every company is now sitting with a pile of data and does not really know what to do with that data. So, to organize this volume of data and draw meaningful insights from it, they require people who are experts in Data Science.

Organizations (irrespective of their size) are on the lookout of those employees who can fathom as well as synthesize data and then, in turn, communicate those very outcomes in a method that serves advantageous to the organization and assists the management in making decisions.

A data scientist can work in any global location. In addition, along with the technology industry, a data scientist can work in different industries as well as domains, ranging from pharma/healthcare to sales/marketing. They can also work in domains like consulting, financial services, CPG industries, and retail.

Apart from the above-mentioned uses, data science has proven to solve many complex real-time problems. A few examples of the real-world problems which have found peace in the modern-day data-driven solutions are:

· Advancement in the field of data science has made it easier to detect fraud and abuse in insurance firms now. The credit card fraud detection system works on similar grounds. It protects the security of customers, thus, minimizing losses due to fraud.

· Automated piloting: The concept behind self-driven vehicles runs on data science. Still, in its nascent stage, this will change the functioning of the automobile industry entirely.

· Prediction of short term (local) and long term (global) weather.

The demand for professionals in data is increasing due to the rise in the popularity of data-driven decision making. Where people used Excel to work on data earlier, tools like Hadoop have nowadays secured a place for managing Big Data. With frequent advancement in technology, several other tools find a meaningful use for organizations to make impactful decisions. The usage of a few is listed below:

· Tools like Python and R have witnessed exceptional improvements in their codes. These allow users to solve complex problems with only a few lines of codes.

· Google Analytics is another effective tool for the marketing department.

· Tools like Tableau, Microsoft Power BI and Sisense have found relevance in the business intelligence departments for the purpose of data visualization.

Nowadays, there are plenty of options for data science training that one can opt for. There are many institutes offering data science courses and I would recommend you to enrol in Technogeeks data science program, they offer the best combination of data science courses which are in demand and the course which they offer is provided by working IT professionals.

Will Artificial Intelligence Take Care of Us or Destroy Us?

From SIRI to self-driving cars, artificial intelligence (AI) is progressing rapidly. While science fiction often portrays AI as robots with human-like characteristics, AI can encompass anything from Google’s search algorithms to IBM’s Watson to autonomous weapons.

Artificial intelligence today is properly known as narrow AI (or weak AI), in that it is designed to perform a narrow task (e.g. only facial recognition or only internet searches or only driving a car). However, the long-term goal of many researchers is to create general AI (AGI or strong AI). While narrow AI may outperform humans at whatever its specific task is, like playing chess or solving equations, AGI would outperform humans at nearly every cognitive task.

Today, the most popular A.I. techniques are machine learning and its younger cousin, deep learning. Unlike computer programs that rigidly follow rules written by humans, both machine learning and deep learning algorithms can look at a dataset, learn from it, and make new predictions. Deep learning in particular can make impressive predictions by discovering data patterns that people might miss.

People say these machines will be benevolent. They will be perfect. They will truly be these beautiful, benevolent, creatures. I don't think that is accurate and I don't think that they are going to be terminating, baby-eating machines either. These machines are going to reflect our species and our evolutionary process. Everything we are will end up in these artificially intelligent machines no matter what we do.

It's such a complex and such new technology in a lot of ways. I think we are afraid of ourselves. That is what it is. We are afraid of ourselves and our own unconscious minds. When we are building something that reflects us, it's the one thing we're all afraid to face. We're afraid to face ourselves. Building machines that mirror our consciousness is a very frightening proposition because we have seen how evil people can be.

What we are really talking about here is an artificially intelligent machine that is going to be able to surpass our intelligence level. At a certain point, you can call it a singularity. There will be a certain point where these machines have super-human intelligence. The best-case scenario is that they will be caretakers and they will be our teachers. They will teach us to be a better species. That is what I am hoping for as a techno-optimist.

If you are interested in learning Artificial Intelligence and want to make a career in this field then I would recommend you to enrol in Technogeeks AI program by working IT professionals.

How Does AI Learn Things?

Unlike humans, AI has computational power that allows it to process copious amounts of data. As AI’s tasks continue to become more advanced, there’s also an increase in computational power necessary-which can become expensive. In order to avoid this need, AI was made to be a specific purpose learner. If AI gains the ability to relate data that is similar, it should be able to more efficiently process the data and understand it with a lower amount of power.

AI makes you look better in selfies, prevents blindness, and can even turn water into tastier beer. Tech giants and governments say we’re living in a golden age of AI. Roll out the self-driving cars!

AI is already used in multiple disciplines and industries. These devices are capable of reading, writing, speaking, seeing, and understanding. They are able to recognize emotions, play games, and even debate. Due to these capabilities, AI is often leveraged as a virtual assistant that can help plan meetings; as a tool to simplify the job hunting and hiring processes; and much more.

However, in order for this technology to be able to advance, it needs to be able to learn.

AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn.

ANNs can be trained to recognise patterns in information - including speech, text data, or visual images - and are the basis for a large number of the developments in AI over recent years.

Conventional AI uses input to 'teach' an algorithm about a particular subject by feeding it massive amounts of information.  

Practical applications include Google's language translation services, Facebook's facial recognition software and Snapchat's image altering live filters.

The process of inputting this data can be extremely time consuming and is limited to one type of knowledge.

A new breed of ANNs called Adversarial Neural Networks pits the wits of two AI bots against each other, which allows them to learn from each other.

This approach is designed to speed up the process of learning, as well as refining the output created by AI systems.

If you want to learn artificial intelligence then you can enrol for one of the best resources i.e. Artificial Intelligence Course Technogeeks. This training is led by trainers who are AI experts. Besides, at the end of the training, they also awarded me an AI course completion certificate.

How do I Prepare for Azure Certification?

There are specific examinations that candidates can take to get the certifications directly from Microsoft. These exams have moderate to a very high level of difficulty and require students to prepare thoroughly. Many of the certifications are based on specific roles and tasks related to Azure tools and cloud services. Some of the certifications include Azure Fundamentals, Microsoft Certified: Azure Administrator Associate (AZ:104), Microsoft Certified Azure Developer Associate (AZ:204), Microsoft Azure Architect Technologies (AZ:30), Microsoft Azure Architect Design (AZ-301) and more. Different exams check specific expertise related to cloud management and security for granting the certifications.

Every certification is meant to qualify you for different roles and has different prerequisites and associated exams. Though the preparation technique is similar for most certifications, some certifications require particular attention to certain topics and a modification in preparation techniques.

You can also look at the Microsoft Azure Documentation for getting the base concepts. Especially valuable for beginners, their page contains key insights in fundamental concepts like Agility, Elasticity, Fault Tolerance, High Availability, Scalability and other core features in any cloud network.

It also contains Azure-specific details like computation, security and storage in Azure. Furthermore, it provides a thorough grounding into creating an account in Azure, networking options, application storage, using PowerShell to automate Azure tasks and using the CLI for utilizing Azure services.

After brushing up on the exam fundamentals and acquiring the basics from Microsoft’s own documentation, it is beneficial to join some instructor-led course to obtain further expertise in the topics and for availing the mock-exams such courses usually provide.

Any standard course would provide a thorough grounding in the topics covered in the exam’s syllabus and would also prepare you better by hosting lab sessions where you can hone your practical skills. And I would recommend you to enrol in Technogeeks Microsoft Azure certification training program by working IT professionals.

Another key advantage of instructor-led training is the facility to set up on-demand classroom training. Here, you can arrange classroom training on your convenience such as a live class in person, attending live class remotely, asking questions to the instructor in person and many more.

The Microsoft Azure certification path can be an enriching journey and enable you to pursue a career in the cutting-edge world of the public cloud. With proper preparation and support and with the right instructors, clearing the exams should not be a challenge at all.

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Why is Python considered a good language for AI and Machine Learning?

Python has enjoyed a steady rise to fame over recent years and is now jostling for the position of one of the most popular programming languages in the world. Favoured for applications ranging from web development to scripting and process automation, Python is quickly becoming the top choice among developers for artificial intelligence (AI), machine learning, and deep learning projects.

The high-level, robust programming language focuses on rapid application development. The core functionality has helped Python become one of the fastest-growing programming languages. Here are top reasons why developers and companies working on emerging technologies including AI, and ML tend to choose Python.

Simple code structure:

Python focuses on reducing the number of lines of code that you write to execute a function. The language simplifies the code and makes it readable. The combination of Python and AI will help in reducing the size of code that developers write. The language, if used with AI and ML algorithms, will make it easier to reduce the quantity of code.

Vast Community:

Python is well-known for its extremely vast community. Since its release, the community is contributing largely and which is the reason a Python user never feels abandoned with sudden changes. The constant upgrade by the developer community support makes Python one of the most suitable languages for machine learning applications. Large organisations such as Google, Amazon, Facebook, etc. are using this language.

Frameworks & Libraries:

One thing the developers like most about Python is the abundance of open source libraries and frameworks. The language has a great number of machine learning libraries and some of the prominent libraries are such as TensorFlow, Pytorch, Matplotlib, SciKit Learn, etc. Python has a collection as well as code stack of various open-source repositories in almost every domain such as Django for integrating web applications, pandas for machine learning, SciPy for scientific computing, Librosa for audio, OpenCV for images, NumPy for text, etc. Other commonly used libraries for artificial intelligence and machine learning are such as pyDatalog (Logic Programming engine in Python), PyML (the bilateral framework is written in Python that focuses on SVMs and other kernels methods), EasyAI (Simple Python engine for two-players games with AI), PyBrain (simple and effective algorithm for ML tasks), AIMA (Python implementation of algorithms), simple, etc.

If you are interested in learning AI with Python then I would recommend you to enrol in Tehcnogeeks Artificial Intelligence with Python the program under a working IT professional with hands-on projects.

Is it Worth Learning Data Science in 2021?

Yes, it is worth learning, in recent times, Data Science, an emerging technology, has perhaps been the most discussed term in the Information and Technology industry. Data Science, Machine Learning, and Analytics is considered to be among the hottest career paths. The demand for skilled data science practitioners in industry, academia, and the government is rapidly growing. The ongoing “data rush” is therefore attracting so many professionals with diverse backgrounds such as physics, mathematics, statistics, economics, and engineering.

With the amount of data that is being generated and the evolution in the field of Analytics, Data Science has turned out to be a necessity for companies. Today, more and more organizations, ranging from small scale to large enterprises, have realized the importance of Data Science and are implementing its capabilities to successfully scale up their business to new heights. There is an intense lack of more than 1 million Data Scientists in the approach to 2020. Some of the roles associated with Data Science are as follows:

·        Data Scientist

·        Data Engineer

·        Data Analyst

·        Machine Learning Engineer

·        Statistician.

Data science is the amalgamation of your specialized aptitudes, analytical bent of mind and sharp business keenness making it the job role for the exceptionally skilled and driven having enormous growth opportunities.

We live in a digital world, everything is data-driven. There is data science in business, accounting, education, science, engineering, healthcare, technology, energy sector, government, and so on. So, having the ability to work with data is an essential skill.

You will lead a various group of tech talent, business managers, chiefs, and settle on significant level executive decisions that will legitimately influence the fortunes of the organization putting you directly in the driver’s seat.

By learning the foundations of data science, you can increase your odds of getting a job in the data science field. The question to ask yourself is this: When the opportunity in data science comes knocking at your door, will you be ready? If you have been putting data science off, this is the time to start your journey, do not delay.

There are web-based training institutes that give quality training, profoundly experienced mentors, educational programs in a state of harmony with the industry goals, real industry projects, certifications, and job assistance. And I would suggest you take a look in Technogeeks Data Science program which has well-designed courses which are taught by industry experts and provide complete knowledge about this field.

How do I get an internship as a data scientist in India?

Data Science will always remain an integral part of the culture and economy of the world because Data Science is helpful for companies in many ways. As it helps to understand the customer need in an enhancing manner. The findings and results of Data Science can be applied in every sector like hospitality, travel, education, banking etc. So we can understand the power and requirement of Data Science.

It is accessible for every sector so that there are many requirements of Data Science interns. The requirements you can search for job searching websites.

Now comes on how can you train yourself to be Data Science professional. TECHNOGEEKS in Pune helps you get selected for your dream job. TECHNOGEEKS is an institute which provides training for various courses RPA, AWS, Hadoop, Data Science, Python, Java, Informatica, DevOps, and Angular JS etc.

Why TECHNOGEEKS?

· Our Data Science program is a job oriented program.

· Our training program provides basic to advanced knowledge of every topic.

· Our course design is also as per the industry requirement.

· We provide regular workshop sessions for the practising of students.

· We give a chance to students to interact with industry experts for boosting up their confidence.

· Our faculty is the best trained skilled facility in the field of Data Science.

· We provide training with real-time projects.

· Provide 100% placements assistance and guidance in resume preparation.

Contact us at- 8600998107 or Email us at contact@technogeekscs.co.in

Visit our website for details: technogeekscs.com

Syllabus contents of Data Science are:

The modules covered under Data Science course is:

Section 1 – Introduction to Python

Section 2 – Setting up and installations

Section 3 – Python object and data structures operations

Section 4 – Python statements

Section 5 - UDF functions and methods

Milestone Project - 1

Section 6 - File and exception handling

Section 7 - Python modules and packages

Section 8 – Object-oriented programming

Section 9 - Advanced Python Modules

Section 10 – Package installation and parallel processing

Section 11 – Introduction to Machine learning with Python

Milestone Project – 2

Section 12 - Data Analysis with Python

Section 13 – Data analysis using Numpy

Section 14 – Pandas and advanced analysis

Section 15 – Data visualization with Python

Section 16 Machine learning Algorithms

Section 17 – REST APIs with flask and python

During the course we arrange doubt clearing sessions time to time for a better understanding of the students.

After course completion, we provide a final project which students do by their own under an expert’s guidance.

Hope this helps.

Thanks for reading.

All the best for your future!

 

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What is Data Science? Scope and Career Opportunities

Data Science is trendier nowadays. The name “Data Science”, I think heard by many people. Data refers to information and Science refers to a study of extracted information. So the term Data Science refers to extract information or knowledge from the available data. Many categories come under the Data Science those are machine learning, deep learning, NLP, Python, artificial intelligence, etc.

Data Science is a process where we understand the data, extract information and use it to make a meaningful product out of it. On the basis of this meaningful product, business decisions are made on. Data analyzed by data scientists is called big data. This big data is drawn from many resources and this big data can be divided into two kinds, one is structured data and other is unstructured data. Structured data is easy to understand, sort, read, organize and analyze. A few examples of structured data are data collected from phones, sales data, data related to accounts, website traffic, etc. Whereas unstructured data we can describe as emails, photos, videos, customer reviews, media posts or we can say human input. Unstructured data is very typical to understand, sort, process and analyze. Unstructured data also requires a big investment to manage.

Generally, companies hire data scientists to manage this unstructured data but it is not like that they have to manage unstructured data only, they have also to deal with structured data.

Data Science as a career option: -

Data Science is a fast-growing field, job opening has increased by 75% from 2015 to 2018, even though searches for data scientists' jobs have also increased by 65% in the same span of time.

As we know data shape the business, and for the fast-growing business, there is a need to analyze data and make a meaningful sense of the information. Data science is also helpful for E-commerce as they used to collect more than purchase data, data scientists help to improve customer service and also help to develop products and services. Also in a finance industry data scientists helps to secure data, fraud detection and other major concerns related to debit cards, credit cards and other account transactions. In a social networking field, data science is helping to improve customer satisfaction, establish trends and also helpful to enhance features and other services.

Data Scientist should have the following skills: -

ü Data scientists should be an expert in programming, as it improves statistics skills, helps to analyze data.

ü Quantitative skills are also important for data scientists. It helps to scale your data strategy and implementing machine learning.

ü Product intuition is also an important skill as this helps you to predict system behavior and improve debugging skills.

ü  Communication an important skill for every industry and every individual.

ü Teamwork is also necessary to be a data scientist.

Big Data Training in Pune

Big data technologies are very essential for providing more accurate analysis, which lead to more solid decision making result and cost reductions risks for any business. To handle the power of Big Data, we need to an infrastructure that can process and manage huge volume of data in real-time and protect the privacy and security of these data collections. You can join Big Data Training in Pune to know and learn about big data. Big data is all about to a large amount of data.

Big Data Training in Pune

Big Data is a collection of large data-sets that can't be handled using old computing techniques. To handle Big Data we have to use various tools, techniques, and frameworks which are involved in this techniques. Big data is so critical to managing and procedure and it is one of the most important technologies in the modern world.

The career in Big Data and Hadoop Technology - Read the article on Big Data Certification in Pune

Examples for Big Data Collection:-

Big data produced by different-different applications and devices. Here are some of the areas that come under the Big Data zone.

• Search Engine: Search engines like Google, yahoo or Bing retrieve lots of information from different databases.
• Social Media: Social media such as Twitter and Facebook holds the information and the views posted by billions of people across the world.
• Stock Exchange: The stock exchange data collect the information about the sell and buy decisions on a share market which is generate a big amount of information.
• Transport: Transport data includes distance, availability, model and capacity of a vehicle.

Read Paras Arora's answer to Which is the best institute for Hadoop? on Quora

Big Data Hadoop Training in Pune

Hadoop is an open source framework of Apache which is used to store process and analyze data in very big volume. Hadoop is leading Big Data platform used by top IT organizations like Facebook, Google, Yahoo and many more. To know more about Hadoop visit Big Data Hadoop Training in Pune.

Big Data Hadoop Training in Pune

Modules of Hadoop:-

1. HDFS (Hadoop Distributed File System): HDFS is a distributed file system that takes care of storage segment of Hadoop applications. HDFS distributes multiple replicas of data on compute nodes in cluster.
2. Yarn: This Hadoop framework is used to scheduling and cluster resource management.
3. Map Reduce: This is another framework of Hadoop which is Yarn based system for processing the large amount of data. It takes input data and converts this data into a data set which is computed in Key value pair.
4. Hadoop Common: These are Java libraries. It used to start Hadoop program and other Hadoop modules can access these libraries to process the data.