Machine Learning Practice Problems Python

The machine learning practice process includes the integrations of learning about the thesis beyond the machine learning algorithms and approaches them for solving real-world problems. Here we have only high qualified writers on machine learning areas who are working. Our research editors do multiple revisions so that our paper is free from plagiarism, Grammer errors, spellings, facts etc.…No trace of plagiarism will be found in your manuscript. For all types of machine learning practice problems in python we derive correct methodology to gain our answer.  Python is extensively deployed in machine learning because of its clarity and the strong powerful libraries like scikit-learn TensorFlow, and PyTorch.

We provide a constructive approach for practicing machine learning with python; let us start from simple problems and slowly increasing difficulties:

Beginner Level

  1. Iris Classification:
  • The popular Iris dataset is used by us for classifying the flower types.
  • The libraries we use : scikit-learn
  • Some algorithms like logistic Regression, k-Nearest Neighbours and Support Vector Machine (SVM).
  1. Boston Housing Price Prediction:
  • We forecast the median value of homes in the Boston area.
  • Libraries are : scikit-learn
  • Linear Regression, Decision Trees are the algorithms are uses in this process
  1. Diabetes Progression Prediction:
  • By working with a dataset, we predict diabetes in advance after one year depending on guideline measurements.
  • Scikit-learn is the library that is deployed in this method.
  • The algorithms are Ridge Regression and Lasso Regression.

Intermediate Level

  1. Sentiment Analysis of Movie Reviews:
  • The sentiment of the movie is classified by us as positive or negative reviews.
  • For Natural Language Processing (NLP) pre-processing, we accomplish libraries like scikit-learn, nltk or spacy.
  • Naive Bayes, Random Forest, and LSTM with keras or PyTorch are some of the algorithms used by us.
  1. Handwritten Digit Recognition (MNIST):
  • By utilizing MNIST dataset, we realize the handwritten numbers.
  • TensorFlow or PyTorch are the accommodated libraries in this method.
  • The algorithm we try in this process is Convolutional Neural Networks (CNN).
  1. Stock Prices Prediction:
  • Through historical data, it forecasts the future stock prices.
  • We use pandas for data manipulation, matplotlib for plotting and scikit-learn for performing linear models.
  • ARIMA and LSTM are the approachable algorithms.

Advanced Level

  1. Image Classification with CIFAR-10:
  • This works on more critical image datasets with different classifications of objects.
  • Such used libraries are Tensorflow or PyTorch .
  • We must try algorithms like Deep CNNs, ResNet, or Transfer Learning with pre-trained models.
  1. Natural Language Processing with Transformer Models:
  • Among the transformer models, BERT is utilized by us for performing various NLP tasks like question and answering or text summarization.
  • Libraries that we use are transformers by Hugging Face, TensorFlow and PyTorch .
  1. Forecasting Air Quality Index:
  • Depending on historical data, we predict the Air Quality Index (AQI) of a zone.
  • For time series forecasting, consider libraries like scikit-learn, fbprophet

Real-World Data Challenges

  1. Kaggle Competitions:
  • We must engage in kaggle competitions for solving practical problems with datasets distributed by the companies and associations.
  • Based on the problem statement, we use all extracted libraries.
  1. UCI Machine Learning Repository:
  • A dataset is chosen by us for the UCI storehouse and an attempt to define the problem statement, data pre-processing and then apply ML algorithms for solutions.
  1. Create Our Own Project:
  • Collect our own data or deploy API (Application Programming Interface) for fetching data from the web.
  • First clean the data pre-process and apply machine learning for gaining awareness or making a prediction.


  • Matplotlib or Seaborn libraries used by us for data visualization.
  • Considering data manipulation, we use pandas libraries.
  • For examining the performance of our model, always divide the data into training and test sets.
  • Cross-validation process is employed for the best evaluation model.
  • We practice the hyper parameter tuning with GridSearchCV or RandomizedSearchCV in Scikit-learn.

By practising these types of problems will not only develop our machine learning knowledge, but also it makes us adaptable with the Python ML (Machine Learning) ecosystem.

Customised writing on all areas of machine learning is also possible in as PhD process in not easy and takes a big time we will guide in all its path. Our research proposal writing services helps scholars to define the main objective that needs to be addressed.

Machine Learning Practice Problems Python Topics

Machine Learning Python Projects Thesis Ideas

We deliver well researched thesis machine learning python project thesis writing by our writers without any plagiarism and on time. Thesis writing may be a challenging yet it consumes a lot of time as we are professional in this field for more than 18+ years we know where to start and how to end it flawlessly.

  1. Characterizing children’s conceptual knowledge and computational practices in a critical machine learning educational program
  2. Using machine learning techniques to reduce uncertainty for outpatient appointment scheduling practices in outpatient clinics
  3. IDoser: Improving individualized dosing policies with clinical practice and machine learning
  4. Operations research and machine learning to manage risk and optimize production practices in agriculture: good and bad experience
  5. Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis
  6. Translating promise into practice: a review of machine learning in suicide research and prevention
  7. Potential applications and performance of machine learning techniques and algorithms in clinical practice: A systematic review
  8. Predicting and interpreting cotton yield and its determinants under long-term conservation management practices using machine learning
  9. Machine Learning Methods in Health Economics and Outcomes Research—The PALISADE Checklist: A Good Practices Report of an ISPOR Task Force
  10. Achieving Good Metabolic Control Without Weight Gain with the Systematic Use of GLP-1-RAs and SGLT-2 Inhibitors in Type 2 Diabetes: A Machine-learning Projection Using Data from Clinical Practice
  11. Data science with Vadalog: Knowledge Graphs with machine learning and reasoning in practice
  12. Machine learning with electrocardiograms: A call for guidelines and best practices for ‘stress testing’ algorithms
  13. Metrics for Benchmarking and Uncertainty Quantification: Quality, Applicability, and Best Practices for Machine Learning in Chemistry
  14. Personalized screening and risk profiles for Mild Cognitive Impairment via a Machine Learning Framework: Implications for general practice
  15. On hyperparameter optimization of machine learning algorithms: Theory and practice
  16. Reconciling modern machine-learning practice and the classical bias–variance trade-off
  17. Towards a theory of practice in metaheuristics design: A machine learning perspective
  18. Bayesian inference: An introduction to principles and practice in machine learning
  19. Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities
  20. The role of artificial intelligence and machine learning in wireless networks security: Principle, practice and challenges


How deal with significant issues ?

1. Novel Ideas

Novelty is essential for a PhD degree. Our experts are bringing quality of being novel ideas in the particular research area. It can be only determined by after thorough literature search (state-of-the-art works published in IEEE, Springer, Elsevier, ACM, ScienceDirect, Inderscience, and so on). SCI and SCOPUS journals reviewers and editors will always demand “Novelty” for each publishing work. Our experts have in-depth knowledge in all major and sub-research fields to introduce New Methods and Ideas. MAKING NOVEL IDEAS IS THE ONLY WAY OF WINNING PHD.

2. Plagiarism-Free

To improve the quality and originality of works, we are strictly avoiding plagiarism since plagiarism is not allowed and acceptable for any type journals (SCI, SCI-E, or Scopus) in editorial and reviewer point of view. We have software named as “Anti-Plagiarism Software” that examines the similarity score for documents with good accuracy. We consist of various plagiarism tools like Viper, Turnitin, Students and scholars can get your work in Zero Tolerance to Plagiarism. DONT WORRY ABOUT PHD, WE WILL TAKE CARE OF EVERYTHING.

3. Confidential Info

We intended to keep your personal and technical information in secret and it is a basic worry for all scholars.

  • Technical Info: We never share your technical details to any other scholar since we know the importance of time and resources that are giving us by scholars.
  • Personal Info: We restricted to access scholars personal details by our experts. Our organization leading team will have your basic and necessary info for scholars.


4. Publication

Most of the PhD consultancy services will end their services in Paper Writing, but our is different from others by giving guarantee for both paper writing and publication in reputed journals. With our 18+ year of experience in delivering PhD services, we meet all requirements of journals (reviewers, editors, and editor-in-chief) for rapid publications. From the beginning of paper writing, we lay our smart works. PUBLICATION IS A ROOT FOR PHD DEGREE. WE LIKE A FRUIT FOR GIVING SWEET FEELING FOR ALL SCHOLARS.

5. No Duplication

After completion of your work, it does not available in our library i.e. we erased after completion of your PhD work so we avoid of giving duplicate contents for scholars. This step makes our experts to bringing new ideas, applications, methodologies and algorithms. Our work is more standard, quality and universal. Everything we make it as a new for all scholars. INNOVATION IS THE ABILITY TO SEE THE ORIGINALITY. EXPLORATION IS OUR ENGINE THAT DRIVES INNOVATION SO LET’S ALL GO EXPLORING.

Client Reviews

I ordered a research proposal in the research area of Wireless Communications and it was as very good as I can catch it.

- Aaron

I had wishes to complete implementation using latest software/tools and I had no idea of where to order it. My friend suggested this place and it delivers what I expect.

- Aiza

It really good platform to get all PhD services and I have used it many times because of reasonable price, best customer services, and high quality.

- Amreen

My colleague recommended this service to me and I’m delighted their services. They guide me a lot and given worthy contents for my research paper.

- Andrew

I’m never disappointed at any kind of service. Till I’m work with professional writers and getting lot of opportunities.

- Christopher

Once I am entered this organization I was just felt relax because lots of my colleagues and family relations were suggested to use this service and I received best thesis writing.

- Daniel

I recommend They have professional writers for all type of writing (proposal, paper, thesis, assignment) support at affordable price.

- David

You guys did a great job saved more money and time. I will keep working with you and I recommend to others also.

- Henry

These experts are fast, knowledgeable, and dedicated to work under a short deadline. I had get good conference paper in short span.

- Jacob

Guys! You are the great and real experts for paper writing since it exactly matches with my demand. I will approach again.

- Michael

I am fully satisfied with thesis writing. Thank you for your faultless service and soon I come back again.

- Samuel

Trusted customer service that you offer for me. I don’t have any cons to say.

- Thomas

I was at the edge of my doctorate graduation since my thesis is totally unconnected chapters. You people did a magic and I get my complete thesis!!!

- Abdul Mohammed

Good family environment with collaboration, and lot of hardworking team who actually share their knowledge by offering PhD Services.

- Usman

I enjoyed huge when working with PhD services. I was asked several questions about my system development and I had wondered of smooth, dedication and caring.

- Imran

I had not provided any specific requirements for my proposal work, but you guys are very awesome because I’m received proper proposal. Thank you!

- Bhanuprasad

I was read my entire research proposal and I liked concept suits for my research issues. Thank you so much for your efforts.

- Ghulam Nabi

I am extremely happy with your project development support and source codes are easily understanding and executed.

- Harjeet

Hi!!! You guys supported me a lot. Thank you and I am 100% satisfied with publication service.

- Abhimanyu

I had found this as a wonderful platform for scholars so I highly recommend this service to all. I ordered thesis proposal and they covered everything. Thank you so much!!!

- Gupta