6 Open Source Machine Learning Frameworks and Tools
Open Source tools are an excellent choice for getting started with Machine learning. This article covers some of the top ML frameworks and tools.
... SQL Concepts, Data Modelling Techniques & Data Engineering Concepts is a must Hands on experience in ETL process, Performance optimization techniques is a must. Candidate should have taken part in Architecture design and discussion. Minimum of 2 years of experience in working with batch processing/ real-time systems using various technologies like Databricks, HDFS, Redshift, Hadoop, Elastic MapReduce on AWS, Apache Spark, Hive/Impala and HDFS, Pig, Kafka, Kinesis, Elasticsearch and NoSQL databases Minimum of 2 years of experience working in Datawarehouse or Data Lake Projects in a role beyond just Data consumption. Minimum of 2 years of extensive working knowledge in AWS building scalable solutions. Equivalent level of experience in Azure or Google Cloud is also acceptable M...
Hi Mohd. I hope you are well, I have some Big Data exercises (hive, pig, sed and mapreduce) I would like to know if you can help me
1) Develop an aggregate of these reviews using your knowledge of Hadoop and MapReduce in Microsoft HDInsight. a) Follow the same approach as the Big Data Analytics Workshop (using the wordcount method in HDInsight) to determine the contributory words for each level of rating. b) Present the workflow of using HDInsight (you may use screen captures) along with a summary of findings and any insights for each level of rating. MapReduce documentation for HDInsight is available here 2) Azure data bricks for some insights Provide the following: a) A screen capture of the completed model diagram and any decision you made in training the model. For example, rationale for some of the components used, how many records have been used for training and how many for testing. b) A set of ...
I am looking for a java developer who is -familiar with hadoop architecture and mapreduce scheduling -familiar with modifying the open source packages
...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...
...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...
...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...
...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...
...7910/DVN/HG7NV7 4. Design, implement and run an Oozie workflow to find out a. the 3 airlines with the highest and lowest probability, respectively, of being on schedule; b. the 3 airports with the longest and shortest average taxi time per flight (both in and out), respectively; and c. the most common reason for flight cancellations. • Requirements: 1. Your workflow must contain at least three MapReduce jobs that run in fully distributed mode. 2. Run your workflow to analyze the entire data set (total 22 years from 1987 to 2008) at one time on two VMs first and then gradually increase the system scale to the maximum allowed number of VMs for at least 5 increment steps, and measure each corresponding workflow execution time. 3. Run your workflow to analyze the data in a prog...
Familiarity with Hadoop ecosystem and its components: obviously, a must! Ability to write reliable, manageable, and high-performance code Expertise knowledge of Hadoop HDFS, Hive, Pig, Flume and Sqoop. Working experience in HQL Experience of writing Pig Latin and MapReduce jobs Good knowledge of the concepts of Hadoop. Analytical and problem-solving skills; the implementation of these skills in Big Data domain Understanding of data loading tools such as Flume, Sqoop etc Good knowledge of database principles, practices, structures, and theories
Using ansible, harvest twitter data with geo coordinates using twitter API and put into a couchDB. The CouchDB setup may be a single node or based on a cluster setup. The cloud based solution should use 4 VMs with 8 virtual CPUs and 500Gb of volume storage. The data is then combined with other useful geographic data to produce some visualization summary results using MapReduce.
Write a MapReduce program to analyze the income data extracted from the 1990 U.S. Census data and determine whether most Americans make more than $50,000 or $50,000 or less a year in 1990. Provide the number of people who made more than $50,000 and the number of people who made $50,000 or less. Download data from http://archive.ics.uci.edu/ml/datasets/Census+Income
1 Explain the concept of Big Data and its importance in a modern economy 2 Explain the core architecture and algorithms underpinning big data processing 3 Analyse and visualize large data sets using a range of statistical and big data technologies 4 Critically evaluate, select and employ appropriate tools and technologies for the development of big data applications
Big Data task with the use of python and hadoop using mapreduce techniques
Parsing, Cleaning, and Profiling of the attached file by removing hashtags, emoticons, or any redundant data which is not useful for analysis. And MapReduce output will be on HDFS like the image attached named "Output" but should be clean. Tasks: Dataset: Programming: MapReduce with Java Data profiling: Write MapReduce java code to characterize (profile) the data in each column. Data cleaning: Cleaning and Profiling the tweets by removing hashtags, emoticons, or any redundant data which is not useful for analysis. Write MapReduce java code to ETL (extract, transform, load) data source. Drop some unimportant columns, Normalize data in a column, and Detect badly formatted rows.
...con l’architettura utilizzata in tutta l’azienda. Competenze richieste - Laurea in Informatica, Information Technology o equivalente esperienza tecnica. - Almeno 3 anni di esperienza professionale. - Profonda conoscenza ed esperienza in statistica. - Previa esperienza in programmazione, preferibilmente in Python, Kafka o Java e volontà di apprende nuovi linguaggi. - Competenze su Hadoop v2, MapReduce, HDFS. - Buona conoscenza dei Big Data querying tools. - Esperienza con Spark. -Esperienza nel processare grandi quantità di dati, sia strutturati che non, inclusa l’integrazione di dati che provengono da fonti diverse. - Esperienza con NoSQL databases, come Cassandra o MongoDB. - Esperienza con vari sistemi di messagistica, come Kafka o RabbitMQ Du...
I need some help with a small task completing some beginning steps in Hadoop with python. Come to the chat and I can explain more. It will not take long, the only thing you need is virtualbox and some som python & Hadoop knowledge.
Cleaning and Profiling the tweets by removing hashtags, emoticons, or any redundant data which is not useful for analysis. Organize the use... or any redundant data which is not useful for analysis. Organize the user_location column in a common standard format. Dataset has been attached. Or you can get it from the link below: Tasks: Data profiling: Write MapReduce java code to characterize (profile) the data in each column. Data cleaning: Cleaning and Profiling the tweets by removing hashtags, emoticons, or any redundant data which is not useful for analysis. Write MapReduce java code to ETL (extract, transform, load) data source. Drop some unimportant columns, Normalize data in a column, and Detect badly formatted rows.
Detailed summary must contain the main theme of the paper, the approach considered for the work, limitation, current trend in this area and your own judgement on the weakness of the paper. The article is attached separately with this assignment. Summary must include the following: - Understand the contribution of the paper - Understand the technologies - Analyse the current Trend with respect to each paper - Identify the drawback of the paper - Any alternative improvement - Follow IEEE reference style Must be: Excellent in explanation of problem understanding, explanation of Technologies, explanation of Scope of the work, explanation of limitation of the work, explanation of improvements
Configure hadoop and perform word count on an input file by using mapreduce on multiple nodes (for example - 1 master and 2 slave nodes).Compare the results obtained by changing the block size each time.
I need help with Hadoop, map reduce and spark. deadline is 24 hrs. please see attached files.
...be used for the application created. The approach involves identifying trading signals in financial time series and capturing the risk associated to these. Such an assessment might support a subsequent evaluation of a trading strategy. Requirements: You must use: (i) Google App Engine, (ii) AWS Lambda, and (iii) one of the other scalable services in AWS: Elastic Compute Cloud (EC2), Elastic MapReduce (EMR) or – should you wish to explore – EC2 Container Service (ECS). Subsequent mentions of scalable services in this document mean Lambda plus your choice of (EC2 or EMR or ECS). ii. Your system must offer a persistent front-end through which the user will initialise (create or ‘warm up’, as necessary) and terminate (as necessary to remove any possible conti...
This project is mainly about tracking people which is like a social network friendship recommendation algorithm using MapReduce
1. Write a MapReduce program to find the frequency of each letter, case insensitive, in any input user-specified files. For example, "The quick brown fox jumps over the lazy dog" as input should generate the following output (letter,count) pairs: (T, 2), (H, 1), (E, 3), etc. 2. Your program also must find the total count of letters, case insensitive, from the input. Generate one extra output pair whose key is the string "total" and whose value is the total count of all letters. 3. Test your program against the 3 attached input files. 4. The input and output will be read/written from/into HDFS. 5. Your program must consist of a single file, namely, LetterCount.java. Declare the mapper and reducer classes as inner classes.
1. Write a MapReduce program to find the frequency of each letter, case insensitive, in any input user-specified files. For example, "The quick brown fox jumps over the lazy dog" as input should generate the following output (letter,count) pairs: (T, 2), (H, 1), (E, 3), etc. 2. Your program also must find the total count of letters, case insensitive, from the input. Generate one extra output pair whose key is the string "total" and whose value is the total count of all letters. 3. Test your program against the 3 attached input files. 4. The input and output will be read/written from/into HDFS. 5. Your program must consist of a single file, namely, LetterCount.java. Declare the mapper and reducer classes as inner classes.
Teksands is looking for an experienced Trainer/Mentor on Hadoop Big Data Engineering with excellent knowledge on the following stack: Hadoop (HDFS, MapReduce) Spark Hive Kafka Only experienced candidates should apply. This is a part-time / contract role – classes in evening/flexible timings, 2-3 times per week for 1.5 hours. Mentor’s responsibility is to teach key concepts to the students, guide them in further learning, provide and guide in assignments and projects, helping them crack interviews. About Teksands: We are a Talent Solutions company helping corporates with Sourcing and Skilling for their talent needs through our flagship Bootcamp based program called Lift-Off. Our goal is to develop future-ready workforce out of fresh grads and junior engineers giving...
there are two data sets online retail system, have to write one mapreduce program for both data sets
Write a MapReduce program in Hadoop that implements the single-pass matrix multiplication.
Skills: Java EE, EJB, Spark, marven, ant, hadoop, spring, mapreduce etc and hope you can work with eclipse. We can connect over discord,zoom, skype anything. EC story Create an ANT project, named ec-stats, for simple descriptive statistics.
...warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume). · Understanding of the auxiliary practical concerns in production ML systems. If you are interested and matching as per requirements, kindly share your updated CV and below details Total Experience? Relevant Experience in deep learning frameworks (such as l, Torch, Caffe, Theano) ? Python, Scala, AWS, Azure and Google cloud platforms? Machine Learning? Reporting/analytic tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).? Current Company? Current Location Flexible to work in the office? Current CTC? Expected CTC? Notice Period? (Shortlisting ...
Implement a parallel program in Java to process a set of text documents received as input, evaluating the length of the processed words, as well as arranging the documents according to the length words and the frequency with which they occur. Each word will be associated with a value, depending on the number of letters. The value of a word is determined by a formula based on Fibonacci's row, so how to explain it later. The rank of a document is calculated by summing the values of all the words in this one. In addition, the maximum length word (or words, if any) shall be laid down for each document several with the same maximum length). Following the parting process, the number of letters of each existing word in a document will be determined, obtaining a list of pairs {length, number ...
Implement a parallel program in Java to process a set of text documents received as input, evaluating the length of the processed words, as well as arranging the documents according to the length words and the frequency with which they occur. Each word will be associated with a value, depending on the number of letters. The value of a word is determined by a formula based on Fibonacci's row, so how to explain it later. The rank of a document is calculated by summing the values of all the words in this one. In addition, the maximum length word (or words, if any) shall be laid down for each document several with the same maximum length). Following the parting process, the number of letters of each existing word in a document will be determined, obtaining a list of pairs {length, number ...
. In this project, you will use the IMDB (International Movies) dataset and develop programs to get interesting insights into the dataset using Hadoop map/reduce paradigm. Please use the following links for a better understanding of Hadoop and Map/Reduce () 1. XSEDE Expanse M/R system You will be using the XSEDE Comet system for your project. Your login has been added for usage. Instructions have been given for using Comet. This is a facility supported by NSF for educational usage. Please make sure you stay within the quota for usage which is approximately 500 SU’s per team. You can install Hadoop on your laptop/desktop for developing and testing the code before you run it on Comet
Experience in guiding with Big Data Technology (MapReduce, Hadoop, Spark, Cassandra)
Entrada: tupla (id,termo) em que "id" é o identificador do documento e "termo" é uma palavra do texto já pré-processada. (Pseudocod/Python/PySpark/Spark)
Hi all, Looking for support on below skill set Transition of legacy ETLs with Java and Hive queries to Spark ETLs. Design and develop data processing solutions and custom ETL pipelines for varied data formats like parquet and Avro. Design, develop, test and release ETL mappings, mapplets, workflows using Streamsets, Java MapReduce, Spark and SQL. Let me know if you have experience in it
Desenvolvimento de algoritmo. sobre MapReduce, utilizando Pyspark/Spark...
Write a regular Python program and then write a mapper and reducer for both txt and csv files
Use MapReduce in Hadoop to process CSV data file Time: 16hrs Price: 40usd Details: Agreement on changes if any after submission Everything to be done exactly as mentioned in the files Updates every 4 hours Plagiarism Free
I need help to Use MapReduce in Hadoop to process CSV data file. I will share more details in chat.
I need help tp Use MapReduce in Hadoop to process CSV data file using Python. I will provide more details in chat.
Looking for Expert who is familiar in Mapreduce Programming, should use Scala to develop your MapReduce program. Detailed requirements will be shared in DM Thanks
Looking for Expert who is familiar in Mapreduce Programming, should use Scala to develop your MapReduce program. Detailed requirements will be shared in DM Thanks
Looking for Expert who is familiar in Mapreduce Programming, should use Scala to develop your MapReduce program. Detailed requirements will be shared in DM Thanks
Need someone who is expert in mapreduce, spark and scala maven.
Implement a small Java program for Hadoop that will extract and reduce the information of the dataset. Determine which useful information can be extracted from the set. More details will be shared with the freelancer
I need an NLP project implementation in Mapreduce. More details to be shared with successful freelancer
Need someone who is an expert in scala, MapReduce and spark programming.
Looking for Expert who is familiar in Mapreduce Programming, should use Scala to develop your MapReduce program. Detailed requirements will be shared in DM Thanks
Open Source tools are an excellent choice for getting started with Machine learning. This article covers some of the top ML frameworks and tools.
This article comprises comprehensive information on the disruption of traditional computing by blockchain.