Article: Place the 2 edges that you’re going to seam together in close proximity—roughly 1–2 in (2.5–5.1 cm) apart. This will give you enough space to apply the 2-part epoxy to the edges, but also make it easier to squeeze the pieces together quickly. This also gives you the opportunity to take one more look at how well the 2 pieces match up. Buy a kit with rubber suction cups and metal turnbuckles (which look like very long bolts) that are intended for clamping countertop seams. For each pair of suction cups, thread a turnbuckle through the openings in the top by turning it clockwise. You want the suction cups to be spaced about 4–6 in (10–15 cm) apart on the turnbuckle so you’ll have room to work between and beneath them.  2 pairs of suction cups and 2 turnbuckles should be sufficient for most countertop seams, but you can use 3 or more for longer seams. You can also buy or rent a tool known as a “seam puller” or “seam setter” that uses vacuum pumps to pull and hold the granite pieces together. If you choose one of these, follow the instructions for proper use. Think of it as placing 2 or 3 “bridges” over the seam, with each turnbuckle serving as the bridge span and the suction cups as the bridge piers. Try to space the suction cups an equal distance from the seam—roughly 2–3 in (5.1–7.6 cm) each.  Make sure the suction cups stick well to the granite. Try moistening the underside of each cup with a damp fingertip if needed. After you apply the 2-part epoxy to the seam, you’ll tighten the turnbuckles to pull the pieces of granite tightly together.
Question: What is a summary of what this article is about?
Lay the 2 pieces of granite side-by-side. Thread turnbuckles through 2-3 pairs of suction cups. Stick each pair of suction cups on either side of the granite seam.
Article: When you’re first starting out, try examining and recreating basic projects provided by Scikit-learn, Awesome Machine Learning, PredictionIO, and similar resources. Once you have a solid grasp on how machine learning works in practice, try coming up with your own projects that you can share online or list on a resume.  So you don’t have to spend time collecting data, try using publicly available data sets from places like the UCI Machine Learning Repository and Quandl.  If you can’t come up with a project idea, look for inspiration on websites like GitHub. Kaggle is a dataset database that hosts a variety of machine learning challenges. Some of these are official competitions, which offer monetary prizes, and some are free competitions that simply provide experience. To start out, try completing the beginner competition Titanic: Machine Learning from Disaster. While personal projects and competitions are fun and look great on a resume, they may not teach you the business-specific machine learning skills required by many companies. So you can gain this experience, look for internships or entry-level jobs related to product-focused machine learning. Look for relevant internships on websites like Internships.com.
Question: What is a summary of what this article is about?
Work on personal machine learning projects. Participate in Kaggle knowledge competitions. Apply for a machine learning internship.
Article: healthy diesels make small amounts of black smoke with some white on cold starts.  Sick ones make blue or continuous white. Diesels are generally robust but require a strict schedule of oil changes. Bonus points for proof of maintenance. Again, bonus points for maintenance records and a spare parts kit. Common ailments of gas engines: wet or worn-out electric components, bad points and plugs. If the seller took the trouble to warm up the engine before showing you the boat, it may be because it is hard to start the engine when it is cold.
Question: What is a summary of what this article is about?
Steer clear of rare or very old engines unless you're certain there's an adequate supply of parts. Do the Smoke Test: Check for fuel leaks and a working bilge blower in gasoline engines. Before the seller cranks the engine, check to see if it is already warm.