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How To Add Machine Learning In Resume

Building An Ocr System From Scratch

Project 5: DSA project sorting visualizer PART 2 | projects for resume | creative projects

Optical character recognition is the technique of identifying the letters and digits in a handwritten document or bill. It extracts the relevant information from the documents and records it in the database. Since handwritings come in numerous styles, OCR needs extensive training and fine-tuning of parameters.

Building OCR in Python using YOLO and Tesseract

The dataset for the project is created using the Labellmg tool in python to label all the invoices present. After the labelling, we proceed with the YOLOv4 algorithm to detect the invoice number, date and total bill amount. Next, Tesseract is used to read/predict text from the detected fields. We also use image augmentation to expand the dataset to a considerable size if the dataset is small.

Responsibilities For Machine Learning Software Engineer Resume

  • Strong mathematics and statistics skills
  • Rich knowledge and solid experiences in Machine Learning/ Artificial Intelligence research and applications
  • Strong experience in building Python/R applications
  • Developing plans for deliverables associated with validation and verification
  • Developing novel models and validating them
  • Experience configuring & executing large, complex data pipelines with AWS/GCP/Azure technology stack
  • Experience working with machine learning, ranking infrastructures, and system designs
  • Industry experience building and productionizing innovative end-to-end Machine Learning systems

Machine Learning Systems Internresume Examples & Samples

  • The candidate must be pursuing a BS degree in Computer Science, Computer Engineer, Electrical Engineer, Applied Mathematics or related field
  • At the level of BS the candidate must have Permanent Right to Work in US
  • Minimum 3 months of experience in Machine Learning and Deep learning
  • Minimum 3 months of experience in software development
  • Minimum 3 months of experience Linux, C++, C, Python

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How To Include Computer Technology And Programming Languages In Your Resume

Here are some keywords and transferable skills you can include to score brownie points with employers:

1. Languages Known.

  • Mention any programming languages that you know , along with your proficiency.

2. Projects Completed.

  • Mention previous projects youve completed with your earlier employers.
  • Highlight the languages you used.

3. Helped Write Code.

  • Mention instances when you helped write and execute difficult pieces of code.
  • Explain how it helped your employer with unique computer skills.

4. Performed Feasibility Studies.

  • Mention instances when you used your proficiency to study the feasibility of a project.

5. Implementation Decision.

  • Highlight cases where you determined whether the implementation of a program was feasible or not.
  • Explain how your technical skills helped your organization with metrics to back it up.

Machine Learning Projects On Classification

Top 10 Skills to Become Machine Learning Engineer

Classification refers to labelling groups of data into known categories or classes. Having ML projects on classification listed on your resume help hiring managers to understand your skills on how to tackle any classification problem end-to-end and select the suitable classification machine learning algorithm. Quite similar to classification is clustering but with the minor difference of working with unlabelled data. Clustering defines the process of grouping together identical objects into individual clusters. So, you can add both classification and clustering related machine learning projects to your resume.

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How To Create An Outline For A Machine Learning Resume

A good outline to follow for your machine learning resume is:

  • Header: List your contact information and include links to your portfolio and/or GitHub profile.
  • Profile/Summary: Emphasize key points from your resume that show why you are the best candidate for the role.
  • Experience: Outline your top machine learning successes.
  • Projects: Highlight relevant machine learning projects.
  • Education: Include degrees/certificates/training.
  • Skills: Include relevant technical skills that match the job description.
  • Extra Sections: Add in conferences, published papers, awards and other activities or interests.
  • Machine Learning Validatorresume Examples & Samples

    • Understand the basic building blocks of Machine and Deep Learning stack and develop Integration tests to test the various workflows, for various segments based on requirements and use cases
    • Profile the software stack ,develop and run Performance tests
    • Assess the bottlenecks and help identify areas for optimization in close collaboration with developers
    • Bring a customer perspective to the validation activities and be the customer advocate for usability, setup, etc
    • Min of 3 years programming experience in C++ and Python scripting
    • Understand fundamental Machine learning/ deep learning / neural networks/image processing concepts and use-cases
    • Experience developing integration and system tests

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    How To Build A Good Machine Learning Resume

    Machine learning is a very hot field these days. If you want to build a machine learning resume, you will need to do some projects in the field. However, you can’t just jump into the field without knowing anything about it. We will recommend you to do some pre-work before actually jumping into the machine learning field. You can design a curriculum for getting yourself ramped up for a machine learning role. The curriculum can start with a lot of math, but should go over the fundamentals you need to learn. After that, it should cover different concepts in machine learning. Then it should go over some more math.

    Instructor Machine Learning Universityresume Examples & Samples

    EAPA Digital: Symposium “Recruitment & selection: machine learning & psychometrics” (May 27, 2021)
    • Teach foundational MLU 6-week modules: Teach five, 90-120 minute lectures and project or final exam for each module taught in a 6-week session, integrate practical ML skills in each lesson plan, and coordinate with other instructors to maintain consistency
    • Develop and revise module curriculum: coordinate with Amazon scientists and program staff to enhance the practical relevance of module content and infuse current Amazon ML applications to the learning experience
    • Work with MLU program staff to ensure that students continue receiving a high-quality, university level educational experience while remaining full time Amazon employees
    • Coordinate with other MLU instructors and Teaching Assistants. Support the continuous engagement with Amazon scientists who contribute to the program as instructors and technical consultants
    • Ph.D. or M.S. in computer science, machine learning, mathematics, or related field research in machine learning
    • Teaching experience in higher education as graduate teaching assistant, instructor, or faculty member
    • Ability to teach foundational content in mathematics, linear and logistic regression, and basic data science
    • Strong programming skills

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    Machine Learning Internshipresume Examples & Samples

    • Work with the team in generating training data, model design, feature selection, system implementation, and evaluation
    • Assist in designing and developing a scalable recommendation platform that can be used by various systems/application
    • Apply machine learning and/or graph analysis techniques for a variety of modeling and relevance problems
    • Participate in cutting edge research in machine learning applications
    • Relevant knowledge of machine learning and data mining concepts with an understanding of supervised and unsupervised learning methods
    • Experience developing and debugging in Java on Unix and/or Linux
    • Experience building large-scale server applications
    • Experience with Open source framework such as Hadoop, Hive, Spark, or Oryx
    • Experience working with large data stores

    Key Sections For A Machine Learning Engineer Resume

    A Tailored Resume Summary

    In a competitive field like Machine learning engineer, hiring managers sometimes review hundreds of applications for a single position. Writing a resume that stands out is difficult, so solve that problem by including a compelling introduction for your resume. Begin your resume with a resume objective, which is a 2รข3 sentence paragraph about your job-relevant skills and career goals.

    Machine learning engineer with 4 years of experience in Python, SQL, and Numpy. Proven ability to develop software solutions using data mining and machine learning techniques. Excellent understanding of implementation of solutions using existing software solutions.

    Machine learning engineer with 4 years of experience in Scikit, NLTK, Numpy, Pandas, and Tensor. Proven expertise in handling large datasets, data visualization, and analysis. Achieved superb results in the development and implementation of Machine Learning algorithms that drive significant revenue benefits.

    Machine learning engineer at company C with 4 years of experience in classification and regression using scikit-learn. Expertise in classification and regression with a strong background in classification algorithms, neural networks and deep learning. Passionate about big data and using machine learning models to solve business problems.

    You can read more about how to create a resume summary with artificial intelligence here.

    Your Relevant Professional Experience

    Hard skills to consider

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    Machine Learning Projects For Beginners

    1. Kaggle Titanic Prediction

    The first project on this list is one of the most straightforward ML projects you can take on. This project is recommended to complete beginners in the data industry. The Titanic dataset is available on Kaggle, and the link to download it is given below.

    This dataset is of passengers who traveled on the titanic. It has details like passenger age, ticket fare, cabin, and gender. Based on this information, you will need to predict whether these passengers survived or not.

    It is a simple binary classification problem, and all you need to do is predict if a particular passenger survived. The best thing about this dataset is that all the pre-processing is done for you. You have a nice, clean dataset to train your machine learning model.

    Since this is a classification problem, you can choose to use algorithms like logistic regression, decision trees, and random forests to build the predictive model. You can also choose gradient boosting models like an XGBoost classifier for this beginner-level machine learning project to get better results.

    Dataset: Kaggle Titanic Dataset

    2. House Price Prediction

    House prices data is also great to start with if you are a beginner at machine learning. This project will use the house pricing dataset available on Kaggle. The target variable in this dataset is the price of a particular house, which you will need to predict using information like house area, number of bedrooms, number of bathrooms, and utilities.

    Business Developer For Machine Learning Developmentresume Examples & Samples

    How to Build a Strong Machine Learning Resume
    • Stay connected to customers, customer councils, end users and SAP ecosystem to ensure grass-root level understanding of their current & future needs
    • Ability to capture customer requirements and translate them into software specifications
    • Build business cases to implement solution strategy
    • Contributes to the efficiency, effectiveness and improvement of processes
    • Develop/build story boards for demos of innovation solutions
    • Monitor and analyze technology and industry trends, market research data and customer requirements to identify growth opportunities for SAP
    • Develop and drive solution roadmap and corresponding revenue plan. Build business cases to implement solution strategy
    • Deliver high quality solutions , validation and acceptance of planned and implemented scope adding solution-related non-coded assets and services
    • Create roll out materials e.g. collaterals, references, success stories
    • Actively participate in customer communities. Support strategic deals and customers and partners
    • At least 5 years of solution/business development experiences
    • Experience in develop co-innovation user case with customer
    • Excellent English language skills

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    Skills For Machine Learning Research Engineer Resume

    • Key skills: SQL, Java, Python, NoSQL tool ie: Hadoop, Pig ,Spark, H2O etc
    • Experience working with large scale distributed systems and experience programming in Python, Java and/or R
    • Strong digital portfolio which demonstrates high-level proficiency in design for enterprise and/or consumer audiences
    • Software engineering experience with a demonstrated ability to code
    • + Strong working knowledge and experience working with big data technology e.g. Spark, Hadoop and MapReduce
    • + Effectively communicate technical analyses and results

    Tailor Your Machine Learning Developer Resume And Include Keywords

    As an ML engineer writes algorithms based on the data given for a specific task, you will want to design your machine learning engineer resume based on the job description of a particular engineer position.

    Carefully review the job description to decide whether you should create an AI engineer resume, ML engineer resume, deep learning engineer resume, NLP engineer resume, etc.

    Note: The feature that differentiates a machine learning engineer resume from a machine learning engineer CV is the content. An ML engineer resume will be tailored to a role, while a machine learning CV is usually an outline of all your work accomplishments and educational background.

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    Experience For Machine Learning Engineer Softe Resume

    • Experience and understanding of machine learning techniques
    • Strong background in machine learning, artificial intelligence, data mining
    • Experience developing distributed systems and concurrent programming
    • Research experience, utilizing model evaluation, time series analytics and feature engineering
    • Good exposure in Unsupervised machine learning like clustering, dimensionality reduction, Outlier detection
    • Experience working with Machine Learning frameworks and Data Science methodologies
    • Experience working with machine learning like SciKit-Learn, MLLib, or Theano, in production environments
    • Experience developing neural net models for pattern recognition/natural language processing

    Machine Learning Technology Consultant Midresume Examples & Samples

    Add Machine Learning and Data Science to your Resume in 1 Hour | Ravindrababu Ravula
    • Level decision
    • Makers. Conduct background research to evaluate the feasibility and defense applications of new technological concepts. Produce and present findings and recommendations to a team of colleagues and clients. Assist with technical program management, program development, and briefing materials for government R& D efforts
    • Ability to work in a Fast-paced environment
    • Experience with government

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    High Paying Executive Jobs

    An interesting experiment from researchers at the Carnegie Mellon University a few years ago led to some rather disturbing findings.

    When studying the ad targeting by the worlds leading search engine on third-party websites, they found that what the engine believed were male job seekers, were much more likely to be served with ads for high-paying executive jobs than equivalent female job seekers.

    In this case, the reasons that caused the specific patterns werent particularly clear since the ad-serving system is very complex.

    Responsibilities For Machine Learning Expert Resume

    • Experience guiding teams in addressing the technical and delivery challenges
    • Hands-on experience of Machine Learning and neural networks
    • Hands-on experience in implementing a successful applied industrial software using ML techniques
    • Experience in developing models and/or analytics to support driving efficiencies in operations
    • Experience building services using Play
    • Experience building services using AWS Kinesis, SQS, DynamoDB and RDS

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    Skills For Machine Learning Engineer Fg Resume

    • Experience in data mining, learning to rank, deep learning, natural language processing, machine learning, and/or related fields
    • Experience using statistical modeling or machine learning techniques to build models that have driven company decision making
    • Experience with advanced data analytic techniques, including data mining, machine learning, statistical analysis, or Natural Language Processing
    • Work experience in building and operationalizing various statistical and machine learning models
    • Experience with Apache Spark, streaming technologies , Unix scripting and NOSQL database would be an added advantage

    Software Engineer Machine Learning Buildingresume Examples & Samples

    Machine Learning Resume: Samples and Writing Guide
    • Adapt machine learning techniques from domains such as Vision and Speech to build intelligent user experiences
    • Develop optimized software to run on variety of platforms and environments including mobile, tablet and laptops
    • M.S. or Ph.D in Computer Science and 3+ years of relevant work experience
    • 3+ years of experience in applying machine learning techniques to computer vision and speech recognition domains
    • Experience with scripting languages such as Perl, and Python

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    How To Include Leadership Qualities In Your Resume

    You can take advantage of numerous resume-building tools to highlight your leadership skills.

    For example, you can simply choose a template by Canva that uses the right keywords to demonstrate your leadership skills:

    Resume building tools like Canva come with plenty of templates that come pre-designed with appropriate keywords according to your skill-set.

    Some of its key features are:

    • It has over 6000 resume templates based on specific industries and skill-set.
    • Offers customization of colors, fonts, and layouts.
    • You can click and create boxes to add information.

    Here are some keywords that can help you highlight your leadership capabilities:

    1. Ability to Teach And Mentor.

    • Talks about your ability and experience in teaching and mentoring your team members.
    • Highlights your willingness to lead a team and can be included in your experience section.

    2. Flexibility.

    • You can use this word in a sentence in such a way that it explains how you are flexible about your work and can lead from the front.
    • Explaining how you are willing to make long-term commitments is good to add to a skill section.

    3. Risk-Taker.

    • Highlights how you take or have taken calculated risks in the workplace.

    4. Team-Builder.

    • It explains your ability to select the right employees to build a responsible and responsive team.
    • Here, you can also highlight previous such experiences, either in academic or professional life.

    5. Time Management.

    Skills For Applied Machine Learning Engineer Resume

    • Good communication skills, ability to work with large cross-functional teams of technical and non-technical members and mentor others
    • Excellent written and verbal communication skills, including the ability to develop and deliver presentations
    • Excellent programming skills in python/C++/scala/R
    • Excellent software development skills in one or more of C, C++, or Python
    • Outstanding executive presence and presentation skills
    • Strong background working with machine learning methods and experience in implementing and extending ML algorithms independently

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    Skills For Lead Machine Learning Engineer Resume

    • Experience working in fast-paced environment with 5+ years of related experience
    • Advanced programming skills with Python, Scala, or R,
    • Knowledge and prior experience with some deep learning frameworks is desired by not required
    • Good knowledge and practical experience with OpenCV library
    • Strong expertise and experience in machine learning and data science
    • Strong programming experience with Java, Scala, Python and/or C++
    • Strong hands-on programming experience with Java, Scala, Python and/or C++
    • Proven experience in taking ideas to actual products

    Machine Learning Researcher / Developerresume Examples & Samples

    How to Prepare and Apply for Off Campus Opportunities
    • Bachelors with at least 5 years of experience, or 3 years with a Masters, or 0 years with a PhD within a Science, Technology, Engineering, or Mathematics discipline from an accredited college
    • At least 4 years of research or work experience in deep learning techniques and frameworks
    • Strong Background in Machine Learning
    • Proficient in one or more programming languages such as MATLAB, Java, C++, or Python
    • Familiar with one or more machine learning or statistical modeling toolkits
    • PhD within a Science, Technology, Engineering, or Mathematics discipline from an accredited college
    • Basic understanding of autonomy and artificial intelligence, including multi-agent systems, knowledge representation and reasoning, planning, plan recognition and decision making
    • Experience with multi-player PC or consol gaming
    • Experience programming for GPUs

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