Ladders Referral Hiring Reviews

Scikit-learn Reviews

Ladders Referral Hiring mentions (9)

• 22 Years into a Programming career and feel like I am at a dead end.

  I have been on theladders.com and searching VP, Director of IT, CIO. Not looking at specific companies, just searching the job boards. Source: over 1 year ago

• Lost my first ever real job I've had in life three months in... What do I do??

  Good news. With that degree, you will be in high demand. Look at a data scientist position. Introductory positions are still paying well. Search LinkedIn for entry data scientist. I just checked theladders.com and there are over 7500 open positions needing 0-4 years experience. 154 of them are in Boston. They look to be around $80-100K. That isn't bad scratch for just starting out. Source: over 1 year ago

• How to find different types of exit oppertunities?

  There is a "theladders.com" which a job hunting site, but seems very subscription based and pricy at that. Not too much if you are actually considering a move at the current time, but I'm just hearing people out right now. Right now I am working internal R&D so we don't really have clients. We search out work, make a proof of concept for them, and if chossen, pass it off to someone else. Source: almost 2 years ago

• I have applied to about 10 jobs now and nobody wants to hire

  Well if you want to ruin your day and see why some people don't understand this you should check out theladders.com. It's a site where they make your resume and apply for you. All jobs show salaries, and all jobs reach at least $100K/year in their salary range. You have to pay to use it. Source: about 2 years ago

• Gentlemen, it has been an honor HODLING with you.

  Since there are questions - more like 12-13k a month per salaried gig....to be specific. If you MUST know the art of the hustle - find 2-3 work from home gigs that pay 150-160k a year salary - quit 1 or 2 when you need some time off. They are out there - go on theladders.com and search - but do gigs that are not conflicting (like outside sales / marketing / ops - something that is not going to micromanage you) . Source: about 2 years ago

Scikit-learn mentions (29)

• Essential Deep Learning Checklist: Best Practices Unveiled

  How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 5 days ago

• How to Build a Logistic Regression Model: A Spam-filter Tutorial

  Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 3 months ago

• Link Prediction With node2vec in Physics Collaboration Network

  Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / about 1 year ago

• WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point

  The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago

• PSA: You don't need fancy stuff to do good work.

  Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago